------------------------------------------------------------------------------------------------------------------------------------
      name:  plog_30
       log:  /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/code/do/09_analysis_regional.log
  log type:  text
 opened on:  19 Sep 2022, 11:39:00

. *************************************************
. ********Regional Level Analysis******************
. *************************************************
. 
. * directory definitions 
.         
.         project, doinfo
project PlaceBased_analysis > Project Name: PlaceBased_analysis
project PlaceBased_analysis > Project Dir.: /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication
project PlaceBased_analysis > Build start : 19sep2022, 11:38:37
project PlaceBased_analysis > Do-file Name: 09_analysis_regional.do
project PlaceBased_analysis > Enclosing do-files:
project PlaceBased_analysis >     PlaceBased_analysis.do

.         global pdir "`r(pdir)'"                                                 // the project's main dir.

.         global dofile "`r(dofile)'"                                             // do-file's stub name

.         global data_original = "$pdir/data_original"  //data directory for coded data 

.         global data_coded = "$pdir/data_coded"  //data directory for coded data 

.         global figures = "$pdir/results/figures"  //data directory for figures

.         global tables = "$pdir/results/tables"  //data directory for tables

. 
. * 
.         // report any data we create previously and we do need here: 
.         project, uses("$data_coded/placebased_regional.dta")
project PlaceBased_analysis > do-file uses: "data_coded/placebased_regional.dta" filesig(1029121884:16892740)

.         project, uses("$data_coded/placebased_mapdata.dta")
project PlaceBased_analysis > do-file uses: "data_coded/placebased_mapdata.dta" filesig(331457870:323923)

.         project, uses("$data_coded/placebased_independence.dta")
project PlaceBased_analysis > do-file uses: "data_coded/placebased_independence.dta" filesig(3455068160:3069934)

.         project, uses("$data_coded/placebased_individual.dta")
project PlaceBased_analysis > do-file uses: "data_coded/placebased_individual.dta" filesig(836765086:58113503)

. 
. 
. ***MAINBODY***
. 
. * description:
. 
.         // map of m5s activity (fig 2)
.         use "$data_coded/placebased_m5s_mapdata.dta", clear 

.         spmap treated using "$data_coded/itcoord", id(id) ///
>         ocolor(white ..) osize(none ..) ///
>         fcolor(uzhblue uzhorange) legend(off)

.         ** save as pdf: 
.         graph export "$figures/fig2b_m5s_activity.pdf", replace
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/fig2b_m5s_activity.pdf saved as PDF format

. 
. 
. * open regional level data for analysis below:
. 
.         use "$data_coded/placebased_regional.dta", clear 

. 
. 
. 
.         // histogram (fig 4)
.         summarize referendum_no if m5s_ref_ever==0

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
referendum~o |      7,372    59.32436    8.664603   14.83771   88.23529

.         local m_control=r(mean)

.         summarize referendum_no if m5s_ref_ever==1

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
referendum~o |        622    61.85547    9.368291   35.30427   80.85009

.         local m_treat=r(mean)

. 
.         histogram referendum_no if m5s_ref_ever==0, ///
>         col(uzhblue%50) xtitle(% No in referendum) legend(order(1 "No M5S grassroots" 2 "M5S grassroots")) ///
>         addplot(histogram referendum_no if m5s_ref_ever==1, col(uzhred2%50))  ///
>         xline(`m_control', lcol(uzhblue)) xline( `m_treat', lcol(uzhred2)) ///
>         text(-0.0006 59 "59", place(w) col(uzhblue) size(small)) text(-0.0006  62 "62", place(e) col(uzhred2) size(small))
(bin=38, start=14.837712, width=1.9315152)

.         ***save as pdf: 
.         graph export "$figures/fig4_bivariatescatter.pdf", replace
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/fig4_bivariatescatter.pdf saved as PDF
    format

. 
. 
. 
. 
. * estimation:
.         
.         // define locals: 
.         local controls m5s_c_13 pd_c_13 turnout_13 income unemployment university no_edu foreigners pop_density_16

.         
.         // OLS estimates (tab 1):
.         eststo clear

.         eststo: reghdfe referendum_no m5s_ref_ever, noabsorb cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       5.15
Statistics robust to heteroskedasticity           Prob > F        =     0.0252
                                                  R-squared       =     0.0060
                                                  Adj R-squared   =     0.0059
                                                  Within R-sq.    =     0.0060
Number of clusters (province_id) =        110     Root MSE        =     8.7213

                          (Std. err. adjusted for 110 clusters in province_id)
------------------------------------------------------------------------------
             |               Robust
referendum~o | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
m5s_ref_ever |   2.531104   1.115051     2.27   0.025     .3211096    4.741099
       _cons |   59.32436   .6600825    89.87   0.000      58.0161    60.63263
------------------------------------------------------------------------------
(est1 stored)

.         eststo: reghdfe referendum_no m5s_ref_ever, absorb(province_id) cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       6.13
Statistics robust to heteroskedasticity           Prob > F        =     0.0148
                                                  R-squared       =     0.5572
                                                  Adj R-squared   =     0.5510
                                                  Within R-sq.    =     0.0014
Number of clusters (province_id) =        110     Root MSE        =     5.8612

                          (Std. err. adjusted for 110 clusters in province_id)
------------------------------------------------------------------------------
             |               Robust
referendum~o | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
m5s_ref_ever |   .8628388   .3484211     2.48   0.015     .1722795    1.553398
       _cons |   59.45417   .0271101  2193.07   0.000     59.40044     59.5079
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est2 stored)

.         eststo: reghdfe referendum_no m5s_ref_ever `controls', absorb(province_id)  cluster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  10,    109) =     126.86
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7128
                                                  Adj R-squared   =     0.7083
                                                  Within R-sq.    =     0.3453
Number of clusters (province_id) =        110     Root MSE        =     4.6879

                            (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------
               |               Robust
 referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------+----------------------------------------------------------------
  m5s_ref_ever |   .6478652   .1912101     3.39   0.001     .2688929    1.026837
      m5s_c_13 |   .2464298   .0510771     4.82   0.000     .1451967    .3476629
       pd_c_13 |  -.5135949   .0334354   -15.36   0.000    -.5798627   -.4473271
    turnout_13 |   .0039702   .0355306     0.11   0.911    -.0664503    .0743907
        income |  -.0004784   .0000941    -5.08   0.000     -.000665   -.0002918
  unemployment |   .1771204   .0270597     6.55   0.000     .1234888    .2307519
    university |  -.2616142    .057148    -4.58   0.000    -.3748797   -.1483488
        no_edu |  -.1823652   .0227256    -8.02   0.000    -.2274067   -.1373237
    foreigners |  -.0243882   .0363538    -0.67   0.504    -.0964403    .0476639
pop_density_16 |   .0001967   .0001059     1.86   0.066    -.0000131    .0004065
         _cons |   76.23618   2.059589    37.02   0.000     72.15414    80.31822
--------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est3 stored)

.         ebalance m5s_ref_ever `controls'


Data Setup
Treatment variable:   m5s_ref_ever
Covariate adjustment: m5s_c_13 pd_c_13 turnout_13 income unemployment university no_edu foreigners pop_density_16 

Optimizing...
Iteration 1: Max Difference = 53677.9914
Iteration 2: Max Difference = 19745.0605
Iteration 3: Max Difference = 7261.83395
Iteration 4: Max Difference = 2669.51473
Iteration 5: Max Difference = 980.103505
Iteration 6: Max Difference = 358.627005
Iteration 7: Max Difference = 130.059951
Iteration 8: Max Difference = 46.130041
Iteration 9: Max Difference = 15.5962515
Iteration 10: Max Difference = 4.93874248
Iteration 11: Max Difference = 1.5460966
Iteration 12: Max Difference = .35475118
Iteration 13: Max Difference = .02493076
Iteration 14: Max Difference = .000123282
maximum difference smaller than the tolerance level; convergence achieved


Treated units: 619     total of weights: 619
Control units: 7189    total of weights: 619


Before: without weighting

             |              Treat              |             Control             
             |      mean   variance   skewness |      mean   variance   skewness 
-------------+---------------------------------+---------------------------------
    m5s_c_13 |     20.75      21.51      .2074 |      18.3      35.11     .03357 
     pd_c_13 |      19.5       53.4      1.046 |      18.6       42.1       .702 
  turnout_13 |     74.54      49.11     -.7995 |     74.68      61.76      -.954 
      income |     11955   1.20e+07      .2146 |     11995    9083129     .04957 
unemployment |     13.22      45.64       .736 |     10.07       38.7      1.257 
  university |     9.366      12.36      1.069 |     6.903      5.614      1.146 
      no_edu |     28.56      30.83      .7078 |     33.66      57.14      1.063 
  foreigners |     7.465      21.47      .5777 |     6.556      19.47      1.011 
pop_densi~16 |     891.1    1834514      3.897 |     259.1     282806      7.436 


After:  _webal as the weighting variable

             |              Treat              |             Control             
             |      mean   variance   skewness |      mean   variance   skewness 
-------------+---------------------------------+---------------------------------
    m5s_c_13 |     20.75      21.51      .2074 |     20.75      30.74      .2474 
     pd_c_13 |      19.5       53.4      1.046 |      19.5      38.15      .8164 
  turnout_13 |     74.54      49.11     -.7995 |     74.54      56.69     -.9325 
      income |     11955   1.20e+07      .2146 |     11955   1.50e+07      1.027 
unemployment |     13.22      45.64       .736 |     13.22      58.19      .8788 
  university |     9.366      12.36      1.069 |     9.366       15.6      1.594 
      no_edu |     28.56      30.83      .7078 |     28.56      33.84      .5679 
  foreigners |     7.465      21.47      .5777 |     7.465      29.87      1.226 
pop_densi~16 |     891.1    1834514      3.897 |     891.1    3468613      3.859 

.         reghdfe referendum_no m5s_ref_ever `controls' [aweight=_webal], absorb(province_id)  cluster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  10,    109) =     192.69
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8676
                                                  Adj R-squared   =     0.8656
                                                  Within R-sq.    =     0.5223
Number of clusters (province_id) =        110     Root MSE        =     3.2647

                            (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------
               |               Robust
 referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------+----------------------------------------------------------------
  m5s_ref_ever |   .5178925   .1629074     3.18   0.002     .1950154    .8407696
      m5s_c_13 |   .2059278   .0444714     4.63   0.000     .1177869    .2940687
       pd_c_13 |  -.4850686   .0289076   -16.78   0.000    -.5423627   -.4277746
    turnout_13 |  -.0622131   .0562531    -1.11   0.271     -.173705    .0492788
        income |  -.0006717   .0001052    -6.38   0.000    -.0008802   -.0004632
  unemployment |   .1292213   .0275983     4.68   0.000     .0745223    .1839203
    university |  -.2561137   .0605319    -4.23   0.000    -.3760859   -.1361414
        no_edu |  -.3128671   .0315563    -9.91   0.000    -.3754108   -.2503235
    foreigners |  -.1016216    .029448    -3.45   0.001    -.1599867   -.0432565
pop_density_16 |    .000135    .000049     2.75   0.007     .0000378    .0002322
         _cons |   89.46727   4.393952    20.36   0.000     80.75861    98.17594
--------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

.         eststo: reghdfe referendum_no m5s_ref_ever [aweight=_webal], absorb(province_id)  cluster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(   1,    109) =       2.98
Statistics robust to heteroskedasticity           Prob > F        =     0.0872
                                                  R-squared       =     0.7231
                                                  Adj R-squared   =     0.7192
                                                  Within R-sq.    =     0.0010
Number of clusters (province_id) =        110     Root MSE        =     4.7184

                          (Std. err. adjusted for 110 clusters in province_id)
------------------------------------------------------------------------------
             |               Robust
referendum~o | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
m5s_ref_ever |   .3352664   .1942776     1.73   0.087    -.0497856    .7203184
       _cons |   61.43944   .0971544   632.39   0.000     61.24688      61.632
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est4 stored)

.         eststo: reghdfe referendum_no std_wn_treat_campaign, noabsorb cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       7.44
Statistics robust to heteroskedasticity           Prob > F        =     0.0074
                                                  R-squared       =     0.0072
                                                  Adj R-squared   =     0.0071
                                                  Within R-sq.    =     0.0072
Number of clusters (province_id) =        110     Root MSE        =     8.7162

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   1.083969    .397446     2.73   0.007     .2962435    1.871694
                _cons |   59.32886   .6621335    89.60   0.000     58.01654    60.64119
---------------------------------------------------------------------------------------
(est5 stored)

.         eststo: reghdfe referendum_no std_wn_treat_campaign, absorb(province_id) cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       7.58
Statistics robust to heteroskedasticity           Prob > F        =     0.0069
                                                  R-squared       =     0.5572
                                                  Adj R-squared   =     0.5510
                                                  Within R-sq.    =     0.0015
Number of clusters (province_id) =        110     Root MSE        =     5.8609

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .3470295    .126073     2.75   0.007     .0971569     .596902
                _cons |   59.45969   .0223823  2656.55   0.000     59.41533    59.50406
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est6 stored)

.         eststo: reghdfe referendum_no std_wn_treat_campaign `controls', absorb(province_id)  cluster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  10,    109) =     126.38
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7127
                                                  Adj R-squared   =     0.7082
                                                  Within R-sq.    =     0.3451
Number of clusters (province_id) =        110     Root MSE        =     4.6887

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2060627   .0760245     2.71   0.008     .0553847    .3567407
             m5s_c_13 |   .2465947   .0512954     4.81   0.000     .1449289    .3482604
              pd_c_13 |  -.5133675   .0334788   -15.33   0.000    -.5797213   -.4470136
           turnout_13 |   .0034561    .035689     0.10   0.923    -.0672784    .0741906
               income |  -.0004788   .0000941    -5.09   0.000    -.0006652   -.0002923
         unemployment |   .1778951   .0270978     6.56   0.000     .1241881    .2316021
           university |    -.25782   .0575571    -4.48   0.000    -.3718964   -.1437437
               no_edu |  -.1826568   .0227176    -8.04   0.000    -.2276823   -.1376313
           foreigners |  -.0238165   .0364951    -0.65   0.515    -.0961486    .0485155
       pop_density_16 |   .0002173   .0001023     2.12   0.036     .0000145    .0004201
                _cons |   76.25067   2.056471    37.08   0.000     72.17482    80.32653
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est7 stored)

.         eststo: reghdfe referendum_no std_wn_treat_campaign [aweight=_webal], absorb(province_id)  cluster(province_id)         
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(   1,    109) =       4.94
Statistics robust to heteroskedasticity           Prob > F        =     0.0283
                                                  R-squared       =     0.7236
                                                  Adj R-squared   =     0.7196
                                                  Within R-sq.    =     0.0026
Number of clusters (province_id) =        110     Root MSE        =     4.7146

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .1932943    .086979     2.22   0.028     .0209048    .3656839
                _cons |   61.38625   .0993769   617.71   0.000     61.18929    61.58322
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est8 stored)

.         ** create a LaTeX Table:
.         estfe est*, labels(province_id "Province FE")   

.         ** save the table:
.         esttab est* using "$tables/tab1_ols_regional.tex", replace  ///
>         indicate( `r(indicate_fe)' "Controls=income", labels(\checkmark)) ///
>         se nobaselevels nostar label se(2) b(2) ///
>         drop(pd_c_13 turnout_13 unemployment university no_edu foreigners pop_density_16) ///
>         stats(N N_clust r2_a r2_a_within rmse, fmt(%9.0f %9.0f %9.2f %9.2f %9.2f)  labels("Obs" "Provinces" "adj.R\$^2$" "adj.R\$^
> 2$ (within)" "RMSE")) ///
>         note("\emph{Note:} Clustered standard errors by province in parentheses. Controls omitted from table: PD: \% votes 2013, \
> % turnout 2013, income per cap, \% unemployed, \% university degree, \% low education, \% foreigners, population density. Same var
> iables used for matching, history omitted from matching.") ///
>         substitute(_ _) 
(output written to /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/tables/tab1_ols_regional.tex)

.         
.         // one town simulation: 100 inhabitants, 0 vs 1 event, 10% rsvp
.         reghdfe referendum_no std_wn_treat_campaign [aweight=_webal], absorb(province_id)  cluster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(   1,    109) =       4.94
Statistics robust to heteroskedasticity           Prob > F        =     0.0283
                                                  R-squared       =     0.7236
                                                  Adj R-squared   =     0.7196
                                                  Within R-sq.    =     0.0026
Number of clusters (province_id) =        110     Root MSE        =     4.7146

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .1932943    .086979     2.22   0.028     .0209048    .3656839
                _cons |   61.38625   .0993769   617.71   0.000     61.18929    61.58322
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

.         dis log((5*10/100)+1)
.40546511

.         margins, at(std_wn_treat_campaign=(0 .40546511))

Adjusted predictions                                     Number of obs = 7,804
Model VCE: Robust

Expression: Linear prediction, predict()
1._at: std_wn_treat_c~n =        0
2._at: std_wn_treat_c~n = .4054651

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   61.38625   .0993769   617.71   0.000     61.19148    61.58103
          2  |   61.46463   .0641099   958.74   0.000     61.33897    61.59028
------------------------------------------------------------------------------

.         dis  61.48344 -  61.41139
.07205

.         * 0.06543
.         margins, at(std_wn_treat_campaign=(0.95 1.79))

Adjusted predictions                                     Number of obs = 7,804
Model VCE: Robust

Expression: Linear prediction, predict()
1._at: std_wn_treat_c~n =  .95
2._at: std_wn_treat_c~n = 1.79

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   61.56988   .0167468  3676.52   0.000     61.53706    61.60271
          2  |   61.73225   .0563156  1096.18   0.000     61.62187    61.84263
------------------------------------------------------------------------------

. 
.         // balance figure (fig 5)
.         ** standardize variables
.         standard2 `controls'

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
std_m5s_c_13 |      7,939    4.53e-10           1  -3.097769   5.325397

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
std2_m5s_~13 |      7,939    2.27e-10          .5  -1.548884   2.662699

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
 mc_m5s_c_13 |      7,939    3.87e-08    5.905199  -18.29294   31.44753

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
log_m5s_c_13 |      7,939    2.907667    .3784752   .1194737   3.929222

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
 std_pd_c_13 |      7,939    3.89e-10           1  -2.686481    5.29286

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
std2_pd_c_13 |      7,939    1.95e-10          .5   -1.34324    2.64643

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  mc_pd_c_13 |      7,939   -6.34e-08     6.59277  -17.71135    34.8946

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
 log_pd_c_13 |      7,939    2.913821    .3690495   .6297776   3.997891

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
std_turno~13 |      7,939    1.48e-10           1  -6.911292   3.234593

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
std2_turn~13 |      7,939    7.38e-11          .5  -3.455646   1.617296

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
mc_turnou~13 |      7,939   -2.98e-08      7.8513  -54.26263   25.39576

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
log_turno~13 |      7,939    4.319605    .1115369   3.060659    4.61512

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  std_income |      7,998   -5.30e-10           1  -2.922717   5.635097

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
 std2_income |      7,998   -2.65e-10          .5  -1.461358   2.817548

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   mc_income |      7,998    8.20e-06    3049.701   -8913.41   17185.36

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
 log_income1 |      7,998    9.360112    .2699642   8.043109    10.2823

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
std_unempl~t |      7,913   -2.04e-10           1  -1.523057   5.054386

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
std2_unemp~t |      7,913   -1.02e-10          .5  -.7615284   2.527193

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
mc_unemplo~t |      7,913   -1.87e-09    6.315525  -9.618903    31.9211

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
log_unempl~t |      7,913    2.278528    .5317763   .4946962   3.765378

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
std_univer~y |      7,939   -7.74e-11           1  -2.529018   7.740403

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
std2_unive~y |      7,939   -3.87e-11          .5  -1.264509   3.870202

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
mc_univers~y |      7,939    1.35e-08    2.575059  -6.512371     19.932

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
log_univer~y |      7,939     2.04224    .3098907   .4519852   3.332768

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  std_no_edu |      7,832    4.05e-10           1  -3.190977   6.911679

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
 std2_no_edu |      7,832    2.03e-10          .5  -1.595489   3.455839

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   mc_no_edu |      7,832   -4.83e-09    7.604208  -24.26486   52.55785

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  log_no_edu |      7,832    3.511561    .2122117   2.303953   4.464026

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
std_foreig~s |      7,965   -5.23e-10           1  -1.481569   6.091333

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
std2_forei~s |      7,965   -2.62e-10          .5  -.7407845   3.045666

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
mc_foreign~s |      7,965    4.17e-09     4.45668  -6.602878   27.14712

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
log_foreig~s |      7,965    1.846227    .6312708          0    3.54818

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
std_pop_d~16 |      7,998   -1.78e-10           1  -.4634755   19.40781

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
std2_pop_~16 |      7,998   -8.90e-11          .5  -.2317378   9.703907

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
mc_pop_de~16 |      7,998    1.51e-06    652.7831   -302.549   12669.09

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
log_pop_d~16 |      7,998    4.751474    1.358009   .5610034   9.470656

.         ** produce balance figures: 
.         eststo clear 

.         foreach var of varlist std_m5s_c_13 std_pd_c_13 std_turnout_13 std_income std_unemployment std_university std_no_edu std_f
> oreigners std_pop_density_16 {
  2.                 rename  m5s_ref_ever `var'_treat
  3.                 eststo raw_`var': reg `var' `var'_treat 
  4.                 rename  `var'_treat m5s_ref_ever 
  5.         }

      Source |       SS           df       MS      Number of obs   =     7,939
-------------+----------------------------------   F(1, 7937)      =    105.49
       Model |  104.116333         1  104.116333   Prob > F        =    0.0000
    Residual |  7833.88366     7,937  .987008147   R-squared       =    0.0131
-------------+----------------------------------   Adj R-squared   =    0.0130
       Total |  7937.99999     7,938  .999999999   Root MSE        =    .99348

------------------------------------------------------------------------------------
      std_m5s_c_13 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
std_m5s_c_13_treat |   .4271117   .0415855    10.27   0.000     .3455931    .5086303
             _cons |  -.0333017   .0116119    -2.87   0.004    -.0560642   -.0105392
------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =     7,939
-------------+----------------------------------   F(1, 7937)      =     12.93
       Model |  12.9125749         1  12.9125749   Prob > F        =    0.0003
    Residual |  7925.08741     7,937  .998499107   R-squared       =    0.0016
-------------+----------------------------------   Adj R-squared   =    0.0015
       Total |  7937.99998     7,938  .999999998   Root MSE        =    .99925

-----------------------------------------------------------------------------------
      std_pd_c_13 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
std_pd_c_13_treat |   .1504141   .0418269     3.60   0.000     .0684223    .2324058
            _cons |  -.0117277   .0116793    -1.00   0.315    -.0346223    .0111669
-----------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =     7,939
-------------+----------------------------------   F(1, 7937)      =      0.04
       Model |  .042202544         1  .042202544   Prob > F        =    0.8372
    Residual |   7937.9578     7,937  1.00012067   R-squared       =    0.0000
-------------+----------------------------------   Adj R-squared   =   -0.0001
       Total |        7938     7,938           1   Root MSE        =    1.0001

--------------------------------------------------------------------------------------
      std_turnout_13 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_turnout_13_treat |  -.0085991   .0418609    -0.21   0.837    -.0906574    .0734592
               _cons |   .0006705   .0116888     0.06   0.954    -.0222427    .0235836
--------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =     7,998
-------------+----------------------------------   F(1, 7996)      =      0.35
       Model |  .350097398         1  .350097398   Prob > F        =    0.5541
    Residual |  7996.64991     7,996  1.00008128   R-squared       =    0.0000
-------------+----------------------------------   Adj R-squared   =   -0.0001
       Total |  7997.00001     7,997           1   Root MSE        =         1

----------------------------------------------------------------------------------
      std_income | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
std_income_treat |  -.0247047   .0417544    -0.59   0.554    -.1065543    .0571449
           _cons |   .0019213   .0116441     0.16   0.869    -.0209043    .0247468
----------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =     7,913
-------------+----------------------------------   F(1, 7911)      =    150.69
       Model |  147.894813         1  147.894813   Prob > F        =    0.0000
    Residual |   7764.1052     7,911  .981431576   R-squared       =    0.0187
-------------+----------------------------------   Adj R-squared   =    0.0186
       Total |  7912.00001     7,912           1   Root MSE        =    .99067

----------------------------------------------------------------------------------------
      std_unemployment | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-----------------------+----------------------------------------------------------------
std_unemployment_treat |   .5091185   .0414737    12.28   0.000     .4278191    .5904178
                 _cons |  -.0398262   .0115997    -3.43   0.001    -.0625646   -.0170877
----------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =     7,939
-------------+----------------------------------   F(1, 7937)      =    565.01
       Model |  527.527568         1  527.527568   Prob > F        =    0.0000
    Residual |  7410.47243     7,937  .933661639   R-squared       =    0.0665
-------------+----------------------------------   Adj R-squared   =    0.0663
       Total |  7937.99999     7,938  .999999999   Root MSE        =    .96626

--------------------------------------------------------------------------------------
      std_university | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_university_treat |   .9614011   .0404461    23.77   0.000     .8821161    1.040686
               _cons |    -.07496   .0112938    -6.64   0.000    -.0970988   -.0528212
--------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =     7,832
-------------+----------------------------------   F(1, 7830)      =    267.97
       Model |  259.137381         1  259.137381   Prob > F        =    0.0000
    Residual |  7571.86263     7,830  .967032264   R-squared       =    0.0331
-------------+----------------------------------   Adj R-squared   =    0.0330
       Total |  7831.00001     7,831           1   Root MSE        =    .98338

----------------------------------------------------------------------------------
      std_no_edu | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
std_no_edu_treat |  -.6742145   .0411864   -16.37   0.000    -.7549508   -.5934782
           _cons |   .0532864   .0115788     4.60   0.000     .0305889    .0759838
----------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =     7,965
-------------+----------------------------------   F(1, 7963)      =     25.55
       Model |  25.4672096         1  25.4672096   Prob > F        =    0.0000
    Residual |  7938.53279     7,963  .996927388   R-squared       =    0.0032
-------------+----------------------------------   Adj R-squared   =    0.0031
       Total |        7964     7,964           1   Root MSE        =    .99846

--------------------------------------------------------------------------------------
      std_foreigners | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_foreigners_treat |   .2107423   .0416958     5.05   0.000     .1290075     .292477
               _cons |  -.0164572   .0116519    -1.41   0.158    -.0392979    .0063835
--------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =     7,998
-------------+----------------------------------   F(1, 7996)      =    580.68
       Model |  541.436047         1  541.436047   Prob > F        =    0.0000
    Residual |  7455.56391     7,996  .932411694   R-squared       =    0.0677
-------------+----------------------------------   Adj R-squared   =    0.0676
       Total |  7996.99995     7,997  .999999994   Root MSE        =    .96561

------------------------------------------------------------------------------------------
      std_pop_density_16 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------------------+----------------------------------------------------------------
std_pop_density_16_treat |   .9715354   .0403171    24.10   0.000     .8925035    1.050567
                   _cons |  -.0755558   .0112433    -6.72   0.000    -.0975955    -.053516
------------------------------------------------------------------------------------------

.         foreach var of varlist std_m5s_c_13 std_pd_c_13 std_turnout_13 std_income std_unemployment std_university std_no_edu std_f
> oreigners std_pop_density_16 { 
  2.                 rename  m5s_ref_ever `var'_treat
  3.                 eststo wgt_`var': reg `var' `var'_treat [aweight=_webal]
  4.                 rename  `var'_treat m5s_ref_ever 
  5.         }
(sum of wgt is 1,238)

      Source |       SS           df       MS      Number of obs   =     7,808
-------------+----------------------------------   F(1, 7806)      =      0.00
       Model |  9.1502e-08         1  9.1502e-08   Prob > F        =    0.9997
    Residual |  5845.29433     7,806  .748820693   R-squared       =    0.0000
-------------+----------------------------------   Adj R-squared   =   -0.0001
       Total |  5845.29433     7,807  .748724777   Root MSE        =    .86534

------------------------------------------------------------------------------------
      std_m5s_c_13 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
std_m5s_c_13_treat |   6.85e-06   .0195861     0.00   1.000    -.0383873    .0384009
             _cons |   .3938032   .0138495    28.43   0.000     .3666544    .4209519
------------------------------------------------------------------------------------
(sum of wgt is 1,238)

      Source |       SS           df       MS      Number of obs   =     7,808
-------------+----------------------------------   F(1, 7806)      =      0.00
       Model |  3.3957e-08         1  3.3957e-08   Prob > F        =    0.9999
    Residual |  8214.74009     7,806   1.0523623   R-squared       =    0.0000
-------------+----------------------------------   Adj R-squared   =   -0.0001
       Total |  8214.74009     7,807   1.0522275   Root MSE        =    1.0258

-----------------------------------------------------------------------------------
      std_pd_c_13 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
std_pd_c_13_treat |   4.17e-06    .023219     0.00   1.000    -.0455112    .0455196
            _cons |   .1386822   .0164183     8.45   0.000      .106498    .1708664
-----------------------------------------------------------------------------------
(sum of wgt is 1,238)

      Source |       SS           df       MS      Number of obs   =     7,808
-------------+----------------------------------   F(1, 7806)      =      0.00
       Model |  3.6292e-08         1  3.6292e-08   Prob > F        =    0.9998
    Residual |  6695.28991     7,806  .857710724   R-squared       =    0.0000
-------------+----------------------------------   Adj R-squared   =   -0.0001
       Total |  6695.28991     7,807   .85760086   Root MSE        =    .92613

--------------------------------------------------------------------------------------
      std_turnout_13 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_turnout_13_treat |   4.31e-06   .0209619     0.00   1.000    -.0410866    .0410952
               _cons |  -.0079329   .0148223    -0.54   0.593    -.0369886    .0211228
--------------------------------------------------------------------------------------
(sum of wgt is 1,238)

      Source |       SS           df       MS      Number of obs   =     7,808
-------------+----------------------------------   F(1, 7806)      =      0.00
       Model |  2.7238e-08         1  2.7238e-08   Prob > F        =    0.9999
    Residual |  11316.5332     7,806  1.44972241   R-squared       =    0.0000
-------------+----------------------------------   Adj R-squared   =   -0.0001
       Total |  11316.5332     7,807  1.44953672   Root MSE        =     1.204

----------------------------------------------------------------------------------
      std_income | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
std_income_treat |   3.74e-06   .0272523     0.00   1.000     -.053418    .0534255
           _cons |  -.0228026   .0192703    -1.18   0.237    -.0605775    .0149722
----------------------------------------------------------------------------------
(sum of wgt is 1,238)

      Source |       SS           df       MS      Number of obs   =     7,808
-------------+----------------------------------   F(1, 7806)      =      0.00
       Model |  4.0531e-08         1  4.0531e-08   Prob > F        =    0.9999
    Residual |  10154.8601     7,806  1.30090445   R-squared       =    0.0000
-------------+----------------------------------   Adj R-squared   =   -0.0001
       Total |  10154.8601     7,807  1.30073781   Root MSE        =    1.1406

----------------------------------------------------------------------------------------
      std_unemployment | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-----------------------+----------------------------------------------------------------
std_unemployment_treat |   4.56e-06   .0258156     0.00   1.000     -.050601    .0506101
                 _cons |   .4692878   .0182544    25.71   0.000     .4335042    .5050713
----------------------------------------------------------------------------------------
(sum of wgt is 1,238)

      Source |       SS           df       MS      Number of obs   =     7,808
-------------+----------------------------------   F(1, 7806)      =      0.00
       Model |  2.5395e-07         1  2.5395e-07   Prob > F        =    0.9997
    Residual |  16450.5845     7,806   2.1074282   R-squared       =    0.0000
-------------+----------------------------------   Adj R-squared   =   -0.0001
       Total |  16450.5845     7,807  2.10715826   Root MSE        =    1.4517

--------------------------------------------------------------------------------------
      std_university | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_university_treat |   .0000114   .0328576     0.00   1.000    -.0643984    .0644212
               _cons |   .8864297   .0232339    38.15   0.000     .8408851    .9319743
--------------------------------------------------------------------------------------
(sum of wgt is 1,238)

      Source |       SS           df       MS      Number of obs   =     7,808
-------------+----------------------------------   F(1, 7806)      =      0.00
       Model |  3.6285e-07         1  3.6285e-07   Prob > F        =    0.9994
    Residual |  4362.46416     7,806  .558860385   R-squared       =    0.0000
-------------+----------------------------------   Adj R-squared   =   -0.0001
       Total |  4362.46416     7,807    .5587888   Root MSE        =    .74757

----------------------------------------------------------------------------------
      std_no_edu | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
std_no_edu_treat |  -.0000136   .0169204    -0.00   0.999    -.0331822     .033155
           _cons |  -.6209145   .0119646   -51.90   0.000    -.6443682   -.5974608
----------------------------------------------------------------------------------
(sum of wgt is 1,238)

      Source |       SS           df       MS      Number of obs   =     7,808
-------------+----------------------------------   F(1, 7806)      =      0.00
       Model |  6.7921e-09         1  6.7921e-09   Prob > F        =    0.9999
    Residual |  10085.3146     7,806  1.29199521   R-squared       =    0.0000
-------------+----------------------------------   Adj R-squared   =   -0.0001
       Total |  10085.3146     7,807  1.29182972   Root MSE        =    1.1367

--------------------------------------------------------------------------------------
      std_foreigners | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_foreigners_treat |   1.86e-06   .0257271     0.00   1.000    -.0504301    .0504338
               _cons |   .1934631   .0181918    10.63   0.000     .1578023    .2291239
--------------------------------------------------------------------------------------
(sum of wgt is 1,238)

      Source |       SS           df       MS      Number of obs   =     7,808
-------------+----------------------------------   F(1, 7806)      =      0.00
       Model |  4.5099e-07         1  4.5099e-07   Prob > F        =    0.9998
    Residual |  48553.6264     7,806  6.22003925   R-squared       =    0.0000
-------------+----------------------------------   Adj R-squared   =   -0.0001
       Total |  48553.6264     7,807  6.21924252   Root MSE        =     2.494

------------------------------------------------------------------------------------------
      std_pop_density_16 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------------------+----------------------------------------------------------------
std_pop_density_16_treat |   .0000152   .0564491     0.00   1.000    -.1106401    .1106705
                   _cons |   .9004876   .0399155    22.56   0.000     .8222425    .9787327
------------------------------------------------------------------------------------------

.         ** coefplot figure: 
.         coefplot ///
>         (raw_*) ///
>         (wgt_*, msymbol(D)) ///
>         , keep(*treat) xline(0) ///
>         ciopts(lwidth(0.4 ..)) mlwidth(medthick) msize(medsmall) mfcolor(white) ///
>         legend(order(2 "raw" 4 "entropy balanced")) ///
>         xtitle("standardized {it:differences} in means") ///
>         grid(none) ///
>         ylabel( ///
>         1 "% M5S vote 2013" ///
>         2 "% PD vote 2013" ///
>         3 "% turnout 2013" ///
>         4 "income per capita" ///
>         5 "% unemployment" ///
>         6 "% university degree" ///
>         7 "% no education" ///
>         8 "% foreigners" ///
>         9 "population density" ///
>         ) 

.         ** save as pdf: 
.         graph export "$figures/fig5_balance.pdf", replace
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/fig5_balance.pdf saved as PDF format

. 
.         // local vs. adjacent (fig 6a)
.         eststo clear 

.         eststo: reghdfe referendum_no std_wn_neigh_treat_campaign if std_wn_treat_campaign==0, absorb(province_id)  cluster(provin
> ce_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,373
Absorbing 1 HDFE group                            F(   1,    109) =       4.03
Statistics robust to heteroskedasticity           Prob > F        =     0.0472
                                                  R-squared       =     0.5366
                                                  Adj R-squared   =     0.5296
                                                  Within R-sq.    =     0.0019
Number of clusters (province_id) =        110     Root MSE        =     5.9436

                                         (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_neigh_treat_campaign |   .1314393   .0654738     2.01   0.047     .0016724    .2612061
                      _cons |   59.15748   .0841481   703.02   0.000      58.9907    59.32426
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est1 stored)

.         eststo: reghdfe referendum_no std_wn_neigh_treat_campaign `controls' if std_wn_treat_campaign==0, absorb(province_id)  clu
> ster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,186
Absorbing 1 HDFE group                            F(  10,    109) =     110.43
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6935
                                                  Adj R-squared   =     0.6883
                                                  Within R-sq.    =     0.3326
Number of clusters (province_id) =        110     Root MSE        =     4.7987

                                         (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_neigh_treat_campaign |   .0268164   .0406653     0.66   0.511     -.053781    .1074138
                   m5s_c_13 |   .2379327   .0472045     5.04   0.000     .1443749    .3314906
                    pd_c_13 |  -.5145737   .0315166   -16.33   0.000    -.5770385   -.4521089
                 turnout_13 |   .0099761   .0340678     0.29   0.770    -.0575451    .0774973
                     income |  -.0004594   .0001007    -4.56   0.000     -.000659   -.0002598
               unemployment |   .1773491   .0283577     6.25   0.000      .121145    .2335533
                 university |  -.2819836   .0593733    -4.75   0.000    -.3996596   -.1643076
                     no_edu |  -.1779025   .0220583    -8.07   0.000    -.2216212   -.1341837
                 foreigners |  -.0232989   .0348983    -0.67   0.506    -.0924662    .0458685
             pop_density_16 |   .0001896   .0001525     1.24   0.216    -.0001126    .0004918
                      _cons |   75.62316   2.119504    35.68   0.000     71.42237    79.82395
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est2 stored)

.         eststo: reghdfe referendum_no std_wn_treat_campaign std_wn_neigh_treat_campaign, absorb(province_id)  cluster(province_id)
>  
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   2,    109) =       4.10
Statistics robust to heteroskedasticity           Prob > F        =     0.0193
                                                  R-squared       =     0.5579
                                                  Adj R-squared   =     0.5517
                                                  Within R-sq.    =     0.0031
Number of clusters (province_id) =        110     Root MSE        =     5.8566

                                         (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
      std_wn_treat_campaign |   .3371568   .1226697     2.75   0.007     .0940295    .5802842
std_wn_neigh_treat_campaign |   .1205892   .0616177     1.96   0.053    -.0015351    .2427136
                      _cons |    59.2945   .0971309   610.46   0.000     59.10199    59.48701
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est3 stored)

.         eststo: reghdfe referendum_no std_wn_treat_campaign std_wn_neigh_treat_campaign `controls', absorb(province_id)  cluster(p
> rovince_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  11,    109) =     114.96
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7127
                                                  Adj R-squared   =     0.7082
                                                  Within R-sq.    =     0.3451
Number of clusters (province_id) =        110     Root MSE        =     4.6890

                                         (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
      std_wn_treat_campaign |   .2067176   .0767888     2.69   0.008     .0545247    .3589105
std_wn_neigh_treat_campaign |   .0160679   .0397852     0.40   0.687    -.0627851    .0949209
                   m5s_c_13 |   .2457353   .0514508     4.78   0.000     .1437616    .3477091
                    pd_c_13 |  -.5134436   .0334685   -15.34   0.000     -.579777   -.4471102
                 turnout_13 |   .0030754   .0357169     0.09   0.932    -.0677143     .073865
                     income |  -.0004796    .000094    -5.10   0.000    -.0006659   -.0002933
               unemployment |   .1775716    .027059     6.56   0.000     .1239415    .2312016
                 university |  -.2575636   .0575666    -4.47   0.000    -.3716588   -.1434684
                     no_edu |   -.182332   .0226256    -8.06   0.000    -.2271752   -.1374888
                 foreigners |  -.0235018   .0363533    -0.65   0.519    -.0955529    .0485493
             pop_density_16 |   .0002124   .0001013     2.10   0.038     .0000117    .0004131
                      _cons |    76.2737   2.060861    37.01   0.000     72.18914    80.35826
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est4 stored)

.         ** coefplot:
.         coefplot ///
>         est1 ///
>         est2 ///
>         (est3, msymbol(S)) ///
>         (est4, msymbol(S)) ///
>         , keep(std_wn_treat_campaign std_wn_neigh_treat_campaign) ///
>         xline(0) ///
>         legend(order(2 "only neighbouring" 4 "+ controls" 6 "neighbouring & local" 8 "+ controls")) ///
>         xtitle("OLS coefficient of [...] on {bf:Referendum: No}") ///
>         ciopts(lwidth(0.4 ..)) mlwidth(medthick) msize(medsmall) mfcolor(white) ///
>         title("{bf:A) local spillovers}") ///
>         ylabel( ///
>         1 "M5S: neighbouring activity cont." ///
>         2 "M5S: activity cont." ///
>         )

.         ** save as pdf: 
.         graph export "$figures/fig6a_spillover_regional.pdf", replace
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/fig6a_spillover_regional.pdf saved as PDF
    format

. 
.         // bystander effect indoor vs. outdoor (fig 7a + tab a11)
.         ** open regional level data:
.         use "$data_coded/placebased_regional.dta", clear 

.         ** estimate: 
.         eststo clear

.         eststo: reghdfe referendum_no std_wn_treat_loc_indoor m5s_c_13 pd_c_13 turnout_13 income unemployment university no_edu fo
> reigners pop_density_16, absorb(province_id) cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  10,    109) =     125.22
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7125
                                                  Adj R-squared   =     0.7080
                                                  Within R-sq.    =     0.3447
Number of clusters (province_id) =        110     Root MSE        =     4.6900

                                     (Std. err. adjusted for 110 clusters in province_id)
-----------------------------------------------------------------------------------------
                        |               Robust
          referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
------------------------+----------------------------------------------------------------
std_wn_treat_loc_indoor |   .2287264   .1434425     1.59   0.114     -.055572    .5130247
               m5s_c_13 |   .2474433   .0512125     4.83   0.000     .1459417    .3489448
                pd_c_13 |  -.5137142   .0334793   -15.34   0.000    -.5800691   -.4473593
             turnout_13 |   .0023393   .0356163     0.07   0.948     -.068251    .0729295
                 income |  -.0004797   .0000944    -5.08   0.000    -.0006667   -.0002927
           unemployment |   .1783884   .0270442     6.60   0.000     .1247877     .231989
             university |  -.2508362   .0581208    -4.32   0.000    -.3660297   -.1356427
                 no_edu |   -.183608    .022766    -8.07   0.000    -.2287295   -.1384865
             foreigners |  -.0229904   .0363811    -0.63   0.529    -.0950965    .0491157
         pop_density_16 |   .0002417   .0001023     2.36   0.020     .0000389    .0004446
                  _cons |   76.32527    2.06147    37.02   0.000      72.2395    80.41103
-----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est1 stored)

.         eststo: reghdfe referendum_no std_wn_treat_loc_outdoor m5s_c_13 pd_c_13 turnout_13 income unemployment university no_edu f
> oreigners pop_density_16, absorb(province_id) cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  10,    109) =     126.98
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7127
                                                  Adj R-squared   =     0.7082
                                                  Within R-sq.    =     0.3451
Number of clusters (province_id) =        110     Root MSE        =     4.6887

                                      (Std. err. adjusted for 110 clusters in province_id)
------------------------------------------------------------------------------------------
                         |               Robust
           referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------------+----------------------------------------------------------------
std_wn_treat_loc_outdoor |   .5926017     .19284     3.07   0.003     .2103992    .9748043
                m5s_c_13 |   .2473229   .0512249     4.83   0.000     .1457967     .348849
                 pd_c_13 |  -.5132505   .0334549   -15.34   0.000     -.579557    -.446944
              turnout_13 |   .0023005   .0356047     0.06   0.949     -.068267    .0728679
                  income |  -.0004788   .0000938    -5.11   0.000    -.0006647    -.000293
            unemployment |   .1787649    .027072     6.60   0.000     .1251092    .2324207
              university |  -.2546047   .0572859    -4.44   0.000    -.3681435   -.1410659
                  no_edu |  -.1832601   .0227506    -8.06   0.000    -.2283511   -.1381692
              foreigners |  -.0230525   .0363301    -0.63   0.527    -.0950575    .0489525
          pop_density_16 |   .0002243   .0001016     2.21   0.029     .0000229    .0004257
                   _cons |   76.31852    2.05978    37.05   0.000      72.2361    80.40094
------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est2 stored)

.         eststo: reghdfe referendum_no std_wn_treat_loc_indoor std_wn_treat_loc_outdoor m5s_c_13 pd_c_13 turnout_13 income unemploy
> ment university no_edu foreigners pop_density_16, absorb(province_id) cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  11,    109) =     118.92
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7127
                                                  Adj R-squared   =     0.7082
                                                  Within R-sq.    =     0.3451
Number of clusters (province_id) =        110     Root MSE        =     4.6890

                                      (Std. err. adjusted for 110 clusters in province_id)
------------------------------------------------------------------------------------------
                         |               Robust
           referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------------+----------------------------------------------------------------
 std_wn_treat_loc_indoor |  -.0676083   .1691313    -0.40   0.690    -.4028211    .2676044
std_wn_treat_loc_outdoor |   .6487852   .2142626     3.03   0.003     .2241237    1.073447
                m5s_c_13 |   .2473959   .0512533     4.83   0.000     .1458135    .3489783
                 pd_c_13 |  -.5132608   .0334534   -15.34   0.000    -.5795643   -.4469574
              turnout_13 |   .0021569   .0356043     0.06   0.952    -.0684097    .0727235
                  income |  -.0004788   .0000937    -5.11   0.000    -.0006645   -.0002931
            unemployment |    .178902   .0270414     6.62   0.000     .1253068    .2324973
              university |  -.2541334   .0576659    -4.41   0.000    -.3684253   -.1398415
                  no_edu |    -.18329    .022765    -8.05   0.000    -.2284095   -.1381706
              foreigners |   -.022875   .0363565    -0.63   0.531    -.0949324    .0491824
          pop_density_16 |    .000225   .0001011     2.23   0.028     .0000247    .0004252
                   _cons |   76.32467   2.058331    37.08   0.000     72.24513    80.40422
------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est3 stored)

.         ** open individual level panel data:
.         use "$data_coded/placebased_individual.dta", clear 

.         xtset 

Panel variable: id (strongly balanced)
 Time variable: wave, 1 to 4, but with gaps
         Delta: 1 unit

.         eststo: reghdfe referendum_no_wunsure std_wave_wn_treat_157d_in, absorb(id post) cluster(id comune_id)
(dropped 116 singleton observations)
(MWFE estimator converged in 2 iterations)

HDFE Linear regression                            Number of obs   =      5,166
Absorbing 2 HDFE groups                           F(   1,   1011) =       0.36
Statistics robust to heteroskedasticity           Prob > F        =     0.5490
                                                  R-squared       =     0.7543
                                                  Adj R-squared   =     0.5080
Number of clusters (id)      =      2,583         Within R-sq.    =     0.0002
Number of clusters (comune_id) =      1,012       Root MSE        =     0.3493

                                    (Std. err. adjusted for 1,012 clusters in id comune_id)
-------------------------------------------------------------------------------------------
                          |               Robust
    referendum_no_wunsure | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
std_wave_wn_treat_157d_in |   .0207085   .0345445     0.60   0.549    -.0470787    .0884956
                    _cons |   .4465264   .0146097    30.56   0.000     .4178576    .4751953
-------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
          id |      2583        2583           0    *|
        post |         2           0           2     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est4 stored)

.         eststo: reghdfe referendum_no_wunsure std_wave_wn_treat_157d_out, absorb(id post) cluster(id comune_id)
(dropped 116 singleton observations)
(MWFE estimator converged in 2 iterations)
Warning: VCV matrix was non-positive semi-definite; adjustment from Cameron, Gelbach & Miller applied.

HDFE Linear regression                            Number of obs   =      5,166
Absorbing 2 HDFE groups                           F(   1,   1011) =      11.14
Statistics robust to heteroskedasticity           Prob > F        =     0.0009
                                                  R-squared       =     0.7550
                                                  Adj R-squared   =     0.5096
Number of clusters (id)      =      2,583         Within R-sq.    =     0.0034
Number of clusters (comune_id) =      1,012       Root MSE        =     0.3488

                                     (Std. err. adjusted for 1,012 clusters in id comune_id)
--------------------------------------------------------------------------------------------
                           |               Robust
     referendum_no_wunsure | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
std_wave_wn_treat_157d_out |   .0839359   .0251465     3.34   0.001     .0345906    .1332813
                     _cons |   .4329893   .0066795    64.82   0.000      .419882    .4460965
--------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
          id |      2583        2583           0    *|
        post |         2           0           2     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est5 stored)

.         eststo: reghdfe referendum_no_wunsure std_wave_wn_treat_157d_in std_wave_wn_treat_157d_out, absorb(id post) cluster(id com
> une_id)
(dropped 116 singleton observations)
(MWFE estimator converged in 2 iterations)
Warning: VCV matrix was non-positive semi-definite; adjustment from Cameron, Gelbach & Miller applied.

HDFE Linear regression                            Number of obs   =      5,166
Absorbing 2 HDFE groups                           F(   2,   1011) =       5.66
Statistics robust to heteroskedasticity           Prob > F        =     0.0036
                                                  R-squared       =     0.7550
                                                  Adj R-squared   =     0.5094
Number of clusters (id)      =      2,583         Within R-sq.    =     0.0034
Number of clusters (comune_id) =      1,012       Root MSE        =     0.3488

                                     (Std. err. adjusted for 1,012 clusters in id comune_id)
--------------------------------------------------------------------------------------------
                           |               Robust
     referendum_no_wunsure | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
 std_wave_wn_treat_157d_in |   .0060211   .0326445     0.18   0.854    -.0580377    .0700798
std_wave_wn_treat_157d_out |   .0827934   .0269121     3.08   0.002     .0299834    .1356033
                     _cons |   .4307463    .013102    32.88   0.000     .4050361    .4564565
--------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
          id |      2583        2583           0    *|
        post |         2           0           2     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est6 stored)

.         ** coefplot:
.         coefplot ///
>         (est1, ) ///
>         (est2, msymbol(S)) ///
>         (est3, msymbol(D)) ///
>         , ///
>         bylabel("{it:referendum result (regional)}") title("{bf:A) bystanders}") ///
>         || ///
>         (est4, rename(std_wave_wn_treat_157d_in = std_wn_treat_loc_indoor)) ///
>         (est5, msymbol(S) rename(std_wave_wn_treat_157d_out = std_wn_treat_loc_outdoor)) ///
>         (est6, msymbol(D) rename(std_wave_wn_treat_157d_in = std_wn_treat_loc_indoor std_wave_wn_treat_157d_out = std_wn_treat_loc
> _outdoor)) ///
>         , ///
>         xline(0) ///
>         xtitle("OLS coefficient of [...] on {bf:Referendum: No}") ///
>         legend(order(2 "indoor" 4 "outdoor" 6 "indoor + outdoor") row(1)) ///
>         bylabel("{it:panel survey (individual)}") byopts(xrescale) /// 
>         ciopts(lwidth(0.4 ..)) mlwidth(medthick) msize(medsmall) mfcolor(white) ///
>         keep(std_wn_treat_loc_indoor std_wn_treat_loc_outdoor std_wave_wn_treat_157d_in std_wave_wn_treat_157d_out) ///
>         ylabel( ///
>         1 "M5S: indoor" ///
>         2 "M5S: outdoor" ///
>         )

.         ** save figure:
.         graph export "$figures/fig7a_bystanders.pdf", as(pdf) name("Graph") replace 
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/fig7a_bystanders.pdf saved as PDF format

.         ** save table:
.         esttab est* using "$tables/taba11_inout.tex", replace  ///
>         indicate( `r(indicate_fe)', labels(\checkmark)) ///
>         rename(std_wave_wn_treat_157d_in std_wn_treat_loc_indoor std_wave_wn_treat_157d_out std_wn_treat_loc_outdoor) ///
>         se nobaselevels nostar label se(2) b(2) ///
>         keep(std_wn_treat_loc_indoor std_wn_treat_loc_outdoor) ///
>         stats(N N_clust2 r2_a r2_a_within rmse,  fmt(%9.0f %9.0f %9.2f %9.2f %9.2f) labels("Obs" "Municipalities" "adj.R\$^2$" "ad
> j.R\$^2$ (within)" "RMSE")) ///
>         note("\emph{Note:} Clustered standard errors by by province (regional) and individual$\times \$ municipality (individual) 
> in parentheses. All controls omitted from table but same as in the mainbody of the text reported in Table 1 and Table 2.") ///
>         substitute(_ _) ///
>         mgroups("regional" "individual", pattern( 0 0 0 1 0 0 0 1) ///
>         prefix(\multicolumn{@span}{c}{) suffix(}) ///
>         span erepeat(\cmidrule(lr){@span})) 
(output written to /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/tables/taba11_inout.tex)

. 
. 
. 
. 
. ***SUPPORTING INFORMATION***
. 
.         use "$data_coded/placebased_regional.dta", clear 

. 
.         // using events only instead of RSVPs (tab a3)
.         cls

.         eststo clear

.         eststo: reghdfe referendum_no std_n_treat_campaign, noabsorb cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       5.08
Statistics robust to heteroskedasticity           Prob > F        =     0.0263
                                                  R-squared       =     0.0050
                                                  Adj R-squared   =     0.0049
                                                  Within R-sq.    =     0.0050
Number of clusters (province_id) =        110     Root MSE        =     8.7256

                                  (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------------
                     |               Robust
       referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_n_treat_campaign |   1.591161   .7062178     2.25   0.026     .1914601    2.990861
               _cons |   59.36667   .6617617    89.71   0.000     58.05508    60.67826
--------------------------------------------------------------------------------------
(est1 stored)

.         eststo: reghdfe referendum_no std_n_treat_campaign, absorb(province_id) cluster(province_id)   
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       5.84
Statistics robust to heteroskedasticity           Prob > F        =     0.0173
                                                  R-squared       =     0.5571
                                                  Adj R-squared   =     0.5509
                                                  Within R-sq.    =     0.0011
Number of clusters (province_id) =        110     Root MSE        =     5.8620

                                  (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------------
                     |               Robust
       referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_n_treat_campaign |   .5202057   .2151917     2.42   0.017     .0937028    .9467085
               _cons |   59.47075   .0209125  2843.79   0.000      59.4293     59.5122
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est2 stored)

.         eststo: reghdfe referendum_no std_n_treat_campaign `controls', absorb(province_id) cluster(province_id)  
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  10,    109) =     125.95
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7126
                                                  Adj R-squared   =     0.7081
                                                  Within R-sq.    =     0.3449
Number of clusters (province_id) =        110     Root MSE        =     4.6894

                                  (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------------
                     |               Robust
       referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_n_treat_campaign |   .2759955   .1245103     2.22   0.029     .0292202    .5227709
            m5s_c_13 |   .2469408    .051229     4.82   0.000     .1454065    .3484751
             pd_c_13 |  -.5136373     .03349   -15.34   0.000    -.5800134   -.4472612
          turnout_13 |   .0028142     .03561     0.08   0.937    -.0677636     .073392
              income |  -.0004791   .0000941    -5.09   0.000    -.0006657   -.0002925
        unemployment |    .178409   .0270913     6.59   0.000     .1247149    .2321031
          university |  -.2536326   .0575214    -4.41   0.000    -.3676382    -.139627
              no_edu |  -.1830126   .0227333    -8.05   0.000    -.2280692    -.137956
          foreigners |  -.0234773   .0363952    -0.65   0.520    -.0956115    .0486569
      pop_density_16 |   .0002299   .0001017     2.26   0.026     .0000283    .0004314
               _cons |   76.28191   2.058701    37.05   0.000     72.20163    80.36219
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est3 stored)

.         ebalance m5s_ref_ever `controls'


Data Setup
Treatment variable:   m5s_ref_ever
Covariate adjustment: m5s_c_13 pd_c_13 turnout_13 income unemployment university no_edu foreigners pop_density_16 

Optimizing...
Iteration 1: Max Difference = 53677.9914
Iteration 2: Max Difference = 19745.0605
Iteration 3: Max Difference = 7261.83395
Iteration 4: Max Difference = 2669.51473
Iteration 5: Max Difference = 980.103505
Iteration 6: Max Difference = 358.627005
Iteration 7: Max Difference = 130.059951
Iteration 8: Max Difference = 46.130041
Iteration 9: Max Difference = 15.5962515
Iteration 10: Max Difference = 4.93874248
Iteration 11: Max Difference = 1.5460966
Iteration 12: Max Difference = .35475118
Iteration 13: Max Difference = .02493076
Iteration 14: Max Difference = .000123282
maximum difference smaller than the tolerance level; convergence achieved


Treated units: 619     total of weights: 619
Control units: 7189    total of weights: 619


Before: without weighting

             |              Treat              |             Control             
             |      mean   variance   skewness |      mean   variance   skewness 
-------------+---------------------------------+---------------------------------
    m5s_c_13 |     20.75      21.51      .2074 |      18.3      35.11     .03357 
     pd_c_13 |      19.5       53.4      1.046 |      18.6       42.1       .702 
  turnout_13 |     74.54      49.11     -.7995 |     74.68      61.76      -.954 
      income |     11955   1.20e+07      .2146 |     11995    9083129     .04957 
unemployment |     13.22      45.64       .736 |     10.07       38.7      1.257 
  university |     9.366      12.36      1.069 |     6.903      5.614      1.146 
      no_edu |     28.56      30.83      .7078 |     33.66      57.14      1.063 
  foreigners |     7.465      21.47      .5777 |     6.556      19.47      1.011 
pop_densi~16 |     891.1    1834514      3.897 |     259.1     282806      7.436 


After:  _webal as the weighting variable

             |              Treat              |             Control             
             |      mean   variance   skewness |      mean   variance   skewness 
-------------+---------------------------------+---------------------------------
    m5s_c_13 |     20.75      21.51      .2074 |     20.75      30.74      .2474 
     pd_c_13 |      19.5       53.4      1.046 |      19.5      38.15      .8164 
  turnout_13 |     74.54      49.11     -.7995 |     74.54      56.69     -.9325 
      income |     11955   1.20e+07      .2146 |     11955   1.50e+07      1.027 
unemployment |     13.22      45.64       .736 |     13.22      58.19      .8788 
  university |     9.366      12.36      1.069 |     9.366       15.6      1.594 
      no_edu |     28.56      30.83      .7078 |     28.56      33.84      .5679 
  foreigners |     7.465      21.47      .5777 |     7.465      29.87      1.226 
pop_densi~16 |     891.1    1834514      3.897 |     891.1    3468613      3.859 

.         eststo: reghdfe referendum_no std_n_treat_campaign [aweight=_webal], absorb(province_id) cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(   1,    109) =       4.25
Statistics robust to heteroskedasticity           Prob > F        =     0.0416
                                                  R-squared       =     0.7235
                                                  Adj R-squared   =     0.7196
                                                  Within R-sq.    =     0.0025
Number of clusters (province_id) =        110     Root MSE        =     4.7149

                                  (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------------
                     |               Robust
       referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_n_treat_campaign |   .3206013   .1555184     2.06   0.042     .0123689    .6288338
               _cons |    61.4068   .0971644   631.99   0.000     61.21422    61.59937
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est4 stored)

.         ***create a LaTeX Table:
.         estfe est*, labels(province_id "Province FE")

.         *
.         esttab est* using "$tables/taba3_events.tex", replace  ///
>         indicate( `r(indicate_fe)' "Controls=income", labels(\checkmark)) ///
>         se nobaselevels nostar label se(2) b(2) ///
>         drop(pd_c_13 turnout_13 unemployment university no_edu foreigners pop_density_16) ///
>         stats(N N_clust r2_a r2_a_within rmse, labels("Obs" "Provinces" "adj.R\$^2$" "adj.R\$^2$ (within)" "RMSE")) ///
>         note("\emph{Note:} Clustered standard errors by province in parentheses. Controls omitted from table: PD: \% votes 2013, \
> % turnout 2013, income per cap, \% unemployed, \% university degree, \% low education, \% foreigners, population density. Same var
> iables used for matching, history omitted from matching.") ///
>         substitute(_ _) 
(output written to /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/tables/taba3_events.tex)

. 
.         // jackknife provinces (fig a2)
.         * estimate: 
.         jackknife, cluster(province_id): reghdfe referendum_no m5s_ref_ever `controls', absorb(province_id) cluster(province_id)
(running reghdfe on estimation sample)

Jackknife replications (110)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..........

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  10,    109) =     118.01
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7128
                                                  Adj R-squared   =     0.7083
                                                  Within R-sq.    =     0.3453
Number of clusters (province_id) =        110     Root MSE        =     4.6879

                             (Replications based on 110 clusters in province_id)
--------------------------------------------------------------------------------
               |              Jackknife
 referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------+----------------------------------------------------------------
  m5s_ref_ever |   .6478652   .1956861     3.31   0.001     .2600217    1.035709
      m5s_c_13 |   .2464298   .0526201     4.68   0.000     .1421385    .3507211
       pd_c_13 |  -.5135949   .0342929   -14.98   0.000    -.5815622   -.4456276
    turnout_13 |   .0039702   .0366591     0.11   0.914     -.068687    .0766274
        income |  -.0004784   .0000997    -4.80   0.000    -.0006759   -.0002808
  unemployment |   .1771204   .0280275     6.32   0.000     .1215708    .2326699
    university |  -.2616142   .0584433    -4.48   0.000    -.3774469   -.1457815
        no_edu |  -.1823652    .023278    -7.83   0.000    -.2285014    -.136229
    foreigners |  -.0243882   .0382602    -0.64   0.525    -.1002187    .0514423
pop_density_16 |   .0001967   .0001181     1.66   0.099    -.0000375    .0004308
         _cons |   76.23618   2.234089    34.12   0.000     71.80829    80.66407
--------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

.         * separately drop provinces: 
.         levelsof province_id, local(levels) 
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 
> 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 9
> 1 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110

.         eststo clear

.         foreach l of local levels {
  2.          eststo pro_`l': reghdfe referendum_no std_wn_treat_campaign `controls' if province_id!=`l', absorb(province_id) cluste
> r(province_id)
  3.         }
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,761
Absorbing 1 HDFE group                            F(  10,    108) =     124.04
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7125
                                                  Adj R-squared   =     0.7080
                                                  Within R-sq.    =     0.3443
Number of clusters (province_id) =        109     Root MSE        =     4.6889

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2099525   .0766802     2.74   0.007      .057959    .3619461
             m5s_c_13 |   .2503688    .051569     4.86   0.000       .14815    .3525875
              pd_c_13 |  -.5123518   .0335827   -15.26   0.000    -.5789186   -.4457851
           turnout_13 |   .0045598   .0358904     0.13   0.899    -.0665811    .0757007
               income |  -.0004805   .0000943    -5.10   0.000    -.0006674   -.0002937
         unemployment |   .1792233   .0275328     6.51   0.000     .1246485    .2337981
           university |  -.2568708   .0577442    -4.45   0.000    -.3713299   -.1424117
               no_edu |  -.1807367   .0227404    -7.95   0.000     -.225812   -.1356613
           foreigners |  -.0241092    .036472    -0.66   0.510    -.0964031    .0481848
       pop_density_16 |   .0002126   .0001027     2.07   0.041     9.07e-06    .0004161
                _cons |   76.00901   2.066924    36.77   0.000       71.912    80.10601
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,618
Absorbing 1 HDFE group                            F(  10,    108) =     125.84
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7179
                                                  Adj R-squared   =     0.7135
                                                  Within R-sq.    =     0.3492
Number of clusters (province_id) =        109     Root MSE        =     4.6794

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2078973   .0767649     2.71   0.008     .0557358    .3600587
             m5s_c_13 |    .247394   .0531601     4.65   0.000     .1420215    .3527665
              pd_c_13 |  -.5159327   .0343605   -15.02   0.000    -.5840412   -.4478242
           turnout_13 |   .0028861   .0368833     0.08   0.938     -.070223    .0759951
               income |  -.0004817   .0000969    -4.97   0.000    -.0006738   -.0002896
         unemployment |   .1814453   .0273821     6.63   0.000     .1271692    .2357214
           university |  -.2522975   .0587893    -4.29   0.000    -.3688282   -.1357668
               no_edu |  -.1836691   .0231024    -7.95   0.000    -.2294619   -.1378762
           foreigners |  -.0256795   .0374294    -0.69   0.494     -.099871     .048512
       pop_density_16 |   .0002102   .0001023     2.06   0.042     7.53e-06     .000413
                _cons |   76.31496   2.094795    36.43   0.000     72.16271     80.4672
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,758
Absorbing 1 HDFE group                            F(  10,    108) =     125.44
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7116
                                                  Adj R-squared   =     0.7072
                                                  Within R-sq.    =     0.3447
Number of clusters (province_id) =        109     Root MSE        =     4.6996

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2019605   .0760246     2.66   0.009     .0512666    .3526544
             m5s_c_13 |   .2470323   .0514085     4.81   0.000     .1451318    .3489328
              pd_c_13 |  -.5138906   .0335576   -15.31   0.000    -.5804077   -.4473736
           turnout_13 |   .0036023   .0357432     0.10   0.920     -.067247    .0744515
               income |  -.0004777   .0000942    -5.07   0.000    -.0006644   -.0002909
         unemployment |   .1779115   .0271428     6.55   0.000     .1241098    .2317132
           university |  -.2592058   .0577879    -4.49   0.000    -.3737516   -.1446601
               no_edu |   -.182416   .0228222    -7.99   0.000    -.2276537   -.1371784
           foreigners |  -.0231113   .0366308    -0.63   0.529      -.09572    .0494974
       pop_density_16 |   .0002161   .0001025     2.11   0.037     .0000129    .0004193
                _cons |   76.24864   2.058699    37.04   0.000     72.16795    80.32934
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,739
Absorbing 1 HDFE group                            F(  10,    108) =     125.48
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7152
                                                  Adj R-squared   =     0.7108
                                                  Within R-sq.    =     0.3483
Number of clusters (province_id) =        109     Root MSE        =     4.6707

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2008392   .0760705     2.64   0.010     .0500543    .3516242
             m5s_c_13 |    .247973   .0517888     4.79   0.000     .1453185    .3506274
              pd_c_13 |  -.5171417   .0335808   -15.40   0.000    -.5837047   -.4505786
           turnout_13 |   .0032187   .0361511     0.09   0.929    -.0684389    .0748764
               income |  -.0004973    .000093    -5.35   0.000    -.0006816    -.000313
         unemployment |   .1762035    .027072     6.51   0.000      .122542     .229865
           university |  -.2394517   .0552617    -4.33   0.000      -.34899   -.1299135
               no_edu |  -.1800375   .0226441    -7.95   0.000     -.224922   -.1351529
           foreigners |  -.0254233   .0367384    -0.69   0.490    -.0982453    .0473987
       pop_density_16 |   .0002193   .0001023     2.14   0.034     .0000165    .0004221
                _cons |   76.34348   2.067106    36.93   0.000     72.24612    80.44084
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,769
Absorbing 1 HDFE group                            F(  10,    108) =     125.98
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7092
                                                  Adj R-squared   =     0.7047
                                                  Within R-sq.    =     0.3453
Number of clusters (province_id) =        109     Root MSE        =     4.6932

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2022911    .076023     2.66   0.009     .0516003     .352982
             m5s_c_13 |    .247165   .0513424     4.81   0.000     .1453954    .3489345
              pd_c_13 |  -.5134475   .0335548   -15.30   0.000    -.5799589   -.4469362
           turnout_13 |   .0024281   .0356925     0.07   0.946    -.0683206    .0731768
               income |  -.0004798   .0000943    -5.09   0.000    -.0006668   -.0002928
         unemployment |   .1778063   .0271065     6.56   0.000     .1240766    .2315361
           university |  -.2572475   .0577449    -4.45   0.000    -.3717079   -.1427871
               no_edu |  -.1825365    .022755    -8.02   0.000    -.2276409   -.1374321
           foreigners |  -.0237544   .0365825    -0.65   0.517    -.0962673    .0487585
       pop_density_16 |   .0002164   .0001023     2.12   0.037     .0000136    .0004193
                _cons |   76.36132   2.057117    37.12   0.000     72.28376    80.43888
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,772
Absorbing 1 HDFE group                            F(  10,    108) =     125.65
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7131
                                                  Adj R-squared   =     0.7087
                                                  Within R-sq.    =     0.3450
Number of clusters (province_id) =        109     Root MSE        =     4.6905

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2056129   .0761011     2.70   0.008     .0547673    .3564585
             m5s_c_13 |   .2468516   .0514428     4.80   0.000      .144883    .3488202
              pd_c_13 |  -.5128889   .0335622   -15.28   0.000     -.579415   -.4463627
           turnout_13 |   .0030711   .0357272     0.09   0.932    -.0677465    .0738886
               income |  -.0004767   .0000943    -5.05   0.000    -.0006638   -.0002897
         unemployment |   .1791182   .0272046     6.58   0.000      .125194    .2330424
           university |  -.2579779   .0578084    -4.46   0.000    -.3725641   -.1433917
               no_edu |  -.1821979   .0227927    -7.99   0.000     -.227377   -.1370189
           foreigners |  -.0223246   .0365217    -0.61   0.542     -.094717    .0500677
       pop_density_16 |   .0002163   .0001026     2.11   0.037      .000013    .0004196
                _cons |   76.21372   2.057705    37.04   0.000     72.13499    80.29245
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,688
Absorbing 1 HDFE group                            F(  10,    108) =     123.85
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7144
                                                  Adj R-squared   =     0.7099
                                                  Within R-sq.    =     0.3459
Number of clusters (province_id) =        109     Root MSE        =     4.6976

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2036525   .0761863     2.67   0.009      .052638    .3546669
             m5s_c_13 |   .2468995       .052     4.75   0.000     .1438264    .3499725
              pd_c_13 |  -.5143178   .0338452   -15.20   0.000    -.5814048   -.4472308
           turnout_13 |   .0080243   .0359358     0.22   0.824    -.0632068    .0792553
               income |  -.0004745   .0000963    -4.93   0.000    -.0006654   -.0002836
         unemployment |   .1798428    .027442     6.55   0.000     .1254479    .2342376
           university |   -.259027   .0585873    -4.42   0.000    -.3751571   -.1428969
               no_edu |  -.1820328   .0230616    -7.89   0.000     -.227745   -.1363207
           foreigners |  -.0191305   .0371067    -0.52   0.607    -.0926824    .0544214
       pop_density_16 |   .0002127   .0001035     2.06   0.042     7.58e-06    .0004178
                _cons |   75.84405   2.035923    37.25   0.000      71.8085     79.8796
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,687
Absorbing 1 HDFE group                            F(  10,    108) =     132.16
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7171
                                                  Adj R-squared   =     0.7127
                                                  Within R-sq.    =     0.3493
Number of clusters (province_id) =        109     Root MSE        =     4.6704

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2040184   .0765495     2.67   0.009      .052284    .3557529
             m5s_c_13 |   .2466798   .0521238     4.73   0.000     .1433614    .3499982
              pd_c_13 |  -.5156143    .034014   -15.16   0.000    -.5830359   -.4481927
           turnout_13 |   .0004361   .0361527     0.01   0.990    -.0712248     .072097
               income |  -.0004809   .0000945    -5.09   0.000    -.0006681   -.0002937
         unemployment |   .1762591    .027955     6.31   0.000     .1208475    .2316707
           university |  -.2679576   .0576251    -4.65   0.000    -.3821806   -.1537347
               no_edu |  -.1847302    .023346    -7.91   0.000     -.231006   -.1384544
           foreigners |  -.0241575    .036684    -0.66   0.512    -.0968716    .0485567
       pop_density_16 |   .0002188    .000102     2.14   0.034     .0000166     .000421
                _cons |   76.70984     2.0435    37.54   0.000     72.65927    80.76041
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,763
Absorbing 1 HDFE group                            F(  10,    108) =     124.96
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7117
                                                  Adj R-squared   =     0.7072
                                                  Within R-sq.    =     0.3445
Number of clusters (province_id) =        109     Root MSE        =     4.6951

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2040108   .0761378     2.68   0.009     .0530926    .3549291
             m5s_c_13 |   .2447798   .0514744     4.76   0.000     .1427487     .346811
              pd_c_13 |  -.5140111   .0335506   -15.32   0.000    -.5805141   -.4475081
           turnout_13 |   .0050728   .0358322     0.14   0.888    -.0659529    .0760985
               income |  -.0004791   .0000942    -5.09   0.000    -.0006658   -.0002925
         unemployment |   .1771462   .0271536     6.52   0.000      .123323    .2309695
           university |  -.2564398   .0576857    -4.45   0.000    -.3707829   -.1420967
               no_edu |  -.1822266   .0227479    -8.01   0.000    -.2273169   -.1371363
           foreigners |  -.0235508   .0365423    -0.64   0.521    -.0959839    .0488823
       pop_density_16 |   .0002117   .0001035     2.05   0.043     6.56e-06    .0004168
                _cons |   76.15107    2.06233    36.92   0.000     72.06317    80.23896
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,794
Absorbing 1 HDFE group                            F(  10,    108) =     126.23
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7125
                                                  Adj R-squared   =     0.7081
                                                  Within R-sq.    =     0.3450
Number of clusters (province_id) =        109     Root MSE        =     4.6912

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2053693   .0764133     2.69   0.008      .053905    .3568337
             m5s_c_13 |   .2467748   .0513273     4.81   0.000     .1450352    .3485143
              pd_c_13 |  -.5133271   .0334878   -15.33   0.000    -.5797059   -.4469484
           turnout_13 |   .0032447   .0357209     0.09   0.928    -.0675603    .0740496
               income |  -.0004791   .0000941    -5.09   0.000    -.0006657   -.0002926
         unemployment |   .1778251   .0271122     6.56   0.000      .124084    .2315663
           university |   -.257653   .0575765    -4.47   0.000    -.3717795   -.1435265
               no_edu |  -.1827062   .0227214    -8.04   0.000    -.2277441   -.1376684
           foreigners |  -.0237997    .036498    -0.65   0.516    -.0961451    .0485456
       pop_density_16 |   .0002173   .0001023     2.12   0.036     .0000145    .0004201
                _cons |   76.26818   2.058692    37.05   0.000     72.18749    80.34886
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,746
Absorbing 1 HDFE group                            F(  10,    108) =     125.08
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7136
                                                  Adj R-squared   =     0.7091
                                                  Within R-sq.    =     0.3450
Number of clusters (province_id) =        109     Root MSE        =     4.6908

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2064623    .076111     2.71   0.008     .0555972    .3573275
             m5s_c_13 |   .2462809   .0514848     4.78   0.000     .1442291    .3483328
              pd_c_13 |  -.5122664   .0336294   -15.23   0.000    -.5789257    -.445607
           turnout_13 |   .0046591   .0359374     0.13   0.897     -.066575    .0758932
               income |  -.0004885   .0000946    -5.16   0.000    -.0006761    -.000301
         unemployment |   .1777724   .0271766     6.54   0.000     .1239037    .2316411
           university |  -.2539726   .0580062    -4.38   0.000    -.3689509   -.1389943
               no_edu |  -.1825699    .022866    -7.98   0.000    -.2278942   -.1372456
           foreigners |  -.0250452    .036778    -0.68   0.497    -.0979456    .0478552
       pop_density_16 |   .0002178   .0001023     2.13   0.036     .0000151    .0004205
                _cons |   76.21741   2.092825    36.42   0.000     72.06906    80.36575
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,726
Absorbing 1 HDFE group                            F(  10,    108) =     124.48
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7140
                                                  Adj R-squared   =     0.7095
                                                  Within R-sq.    =     0.3445
Number of clusters (province_id) =        109     Root MSE        =     4.6803

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2082661   .0764449     2.72   0.008      .056739    .3597931
             m5s_c_13 |   .2524256   .0520778     4.85   0.000     .1491984    .3556529
              pd_c_13 |  -.5114161   .0337907   -15.13   0.000    -.5783952    -.444437
           turnout_13 |   .0005275   .0361141     0.01   0.988    -.0710569    .0721119
               income |  -.0004849   .0000942    -5.15   0.000    -.0006716   -.0002983
         unemployment |   .1716267    .026598     6.45   0.000     .1189048    .2243486
           university |  -.2568682   .0579073    -4.44   0.000    -.3716506   -.1420858
               no_edu |  -.1778496   .0226848    -7.84   0.000    -.2228148   -.1328844
           foreigners |  -.0246204   .0366152    -0.67   0.503    -.0971982    .0479573
       pop_density_16 |   .0002212   .0001028     2.15   0.034     .0000174    .0004251
                _cons |    76.2707   2.071802    36.81   0.000     72.16403    80.37737
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,568
Absorbing 1 HDFE group                            F(  10,    108) =     124.88
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7150
                                                  Adj R-squared   =     0.7105
                                                  Within R-sq.    =     0.3428
Number of clusters (province_id) =        109     Root MSE        =     4.7081

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2132369    .078045     2.73   0.007     .0585382    .3679356
             m5s_c_13 |   .2464464   .0526077     4.68   0.000     .1421689    .3507239
              pd_c_13 |  -.5069204   .0341478   -14.84   0.000    -.5746072   -.4392335
           turnout_13 |  -.0038132   .0357685    -0.11   0.915    -.0747125    .0670862
               income |  -.0004873    .000097    -5.02   0.000    -.0006797    -.000295
         unemployment |   .1776804   .0272786     6.51   0.000     .1236095    .2317514
           university |  -.2480866   .0578918    -4.29   0.000    -.3628382   -.1333349
               no_edu |  -.1861216   .0227666    -8.18   0.000     -.231249   -.1409942
           foreigners |  -.0435578   .0342291    -1.27   0.206    -.1114058    .0242901
       pop_density_16 |    .000212   .0001037     2.04   0.043     6.39e-06    .0004176
                _cons |   77.01112   1.996492    38.57   0.000     73.05373    80.96852
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,731
Absorbing 1 HDFE group                            F(  10,    108) =     125.17
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7142
                                                  Adj R-squared   =     0.7098
                                                  Within R-sq.    =     0.3462
Number of clusters (province_id) =        109     Root MSE        =     4.6871

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2050369   .0761523     2.69   0.008     .0540899    .3559839
             m5s_c_13 |   .2468567    .051525     4.79   0.000     .1447252    .3489881
              pd_c_13 |  -.5145508   .0337404   -15.25   0.000    -.5814302   -.4476714
           turnout_13 |   .0040746   .0359792     0.11   0.910    -.0672424    .0753916
               income |  -.0004929   .0000947    -5.21   0.000    -.0006806   -.0003052
         unemployment |   .1767174   .0271498     6.51   0.000     .1229018     .230533
           university |  -.2503305   .0582095    -4.30   0.000    -.3657118   -.1349492
               no_edu |  -.1821768    .022834    -7.98   0.000    -.2274378   -.1369158
           foreigners |   -.024014    .036701    -0.65   0.514    -.0967617    .0487337
       pop_density_16 |   .0002176   .0001026     2.12   0.036     .0000143    .0004209
                _cons |   76.34968   2.083367    36.65   0.000     72.22009    80.47928
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,751
Absorbing 1 HDFE group                            F(  10,    108) =     125.46
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7094
                                                  Adj R-squared   =     0.7050
                                                  Within R-sq.    =     0.3450
Number of clusters (province_id) =        109     Root MSE        =     4.7001

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2063057   .0762086     2.71   0.008      .055247    .3573644
             m5s_c_13 |   .2467228   .0514522     4.80   0.000     .1447356      .34871
              pd_c_13 |     -.5147   .0335784   -15.33   0.000    -.5812583   -.4481417
           turnout_13 |   .0025359   .0357252     0.07   0.944    -.0682777    .0733495
               income |  -.0004789   .0000942    -5.08   0.000    -.0006657   -.0002921
         unemployment |   .1771856   .0270648     6.55   0.000     .1235384    .2308327
           university |  -.2585229   .0579164    -4.46   0.000    -.3733232   -.1437225
               no_edu |  -.1823484   .0227448    -8.02   0.000    -.2274325   -.1372642
           foreigners |  -.0238444   .0365975    -0.65   0.516     -.096387    .0486982
       pop_density_16 |   .0002144    .000103     2.08   0.040     .0000101    .0004186
                _cons |   76.35859   2.060569    37.06   0.000     72.27418    80.44299
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,694
Absorbing 1 HDFE group                            F(  10,    108) =     133.80
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6705
                                                  Adj R-squared   =     0.6653
                                                  Within R-sq.    =     0.3620
Number of clusters (province_id) =        109     Root MSE        =     4.5921

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2267044   .0733053     3.09   0.003     .0814007    .3720082
             m5s_c_13 |   .2045572   .0327263     6.25   0.000      .139688    .2694263
              pd_c_13 |  -.5364862   .0252268   -21.27   0.000    -.5864901   -.4864823
           turnout_13 |   .0281572   .0273678     1.03   0.306    -.0260906    .0824049
               income |  -.0005204    .000084    -6.20   0.000    -.0006869    -.000354
         unemployment |    .168069   .0250898     6.70   0.000     .1183367    .2178013
           university |  -.2646954    .058113    -4.55   0.000    -.3798854   -.1495054
               no_edu |  -.1894769   .0217224    -8.72   0.000    -.2325344   -.1464195
           foreigners |  -.0491303   .0283196    -1.73   0.086    -.1052647    .0070042
       pop_density_16 |   .0002414   .0000989     2.44   0.016     .0000454    .0004374
                _cons |   77.11127   2.035093    37.89   0.000     73.07736    81.14518
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,600
Absorbing 1 HDFE group                            F(  10,    108) =     121.33
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7151
                                                  Adj R-squared   =     0.7106
                                                  Within R-sq.    =     0.3429
Number of clusters (province_id) =        109     Root MSE        =     4.7103

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2141178   .0776551     2.76   0.007     .0601919    .3680438
             m5s_c_13 |    .250402   .0526501     4.76   0.000     .1460404    .3547636
              pd_c_13 |  -.5113686   .0345159   -14.82   0.000    -.5797851   -.4429522
           turnout_13 |   .0011263   .0363939     0.03   0.975    -.0710128    .0732654
               income |  -.0004727   .0000964    -4.90   0.000    -.0006638   -.0002816
         unemployment |   .1778312   .0272869     6.52   0.000     .1237439    .2319185
           university |  -.2486219   .0578082    -4.30   0.000    -.3632078    -.134036
               no_edu |  -.1814606   .0233107    -7.78   0.000    -.2276664   -.1352547
           foreigners |  -.0184287   .0382719    -0.48   0.631    -.0942902    .0574328
       pop_density_16 |   .0002048   .0001039     1.97   0.051    -1.21e-06    .0004108
                _cons |   76.06316   2.096323    36.28   0.000     71.90789    80.21844
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,784
Absorbing 1 HDFE group                            F(  10,    108) =     125.98
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7120
                                                  Adj R-squared   =     0.7076
                                                  Within R-sq.    =     0.3448
Number of clusters (province_id) =        109     Root MSE        =     4.6927

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2062822   .0760669     2.71   0.008     .0555045    .3570599
             m5s_c_13 |   .2464263   .0513524     4.80   0.000     .1446369    .3482157
              pd_c_13 |  -.5133144   .0335419   -15.30   0.000    -.5798002   -.4468285
           turnout_13 |   .0035311   .0357683     0.10   0.922    -.0673678      .07443
               income |   -.000479   .0000942    -5.09   0.000    -.0006656   -.0002923
         unemployment |   .1780239   .0272521     6.53   0.000     .1240055    .2320423
           university |  -.2573287   .0575951    -4.47   0.000    -.3714922   -.1431652
               no_edu |   -.182295   .0227306    -8.02   0.000    -.2273509    -.137239
           foreigners |  -.0238897   .0365142    -0.65   0.514    -.0962671    .0484877
       pop_density_16 |   .0002175   .0001024     2.12   0.036     .0000145    .0004204
                _cons |   76.22291   2.058774    37.02   0.000     72.14206    80.30375
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,733
Absorbing 1 HDFE group                            F(  10,    108) =     123.23
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7070
                                                  Adj R-squared   =     0.7025
                                                  Within R-sq.    =     0.3431
Number of clusters (province_id) =        109     Root MSE        =     4.6902

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2051021   .0762626     2.69   0.008     .0539363    .3562678
             m5s_c_13 |   .2470671   .0520865     4.74   0.000     .1438226    .3503115
              pd_c_13 |  -.5119857   .0337539   -15.17   0.000    -.5788919   -.4450796
           turnout_13 |   .0025025   .0360968     0.07   0.945    -.0690476    .0740526
               income |  -.0004812   .0000948    -5.08   0.000    -.0006691   -.0002933
         unemployment |     .18371    .027305     6.73   0.000     .1295868    .2378332
           university |  -.2561152   .0579094    -4.42   0.000    -.3709017   -.1413288
               no_edu |  -.1799294   .0227041    -7.92   0.000    -.2249329   -.1349259
           foreigners |   -.024104   .0365349    -0.66   0.511    -.0965224    .0483145
       pop_density_16 |   .0002109   .0001029     2.05   0.043     6.98e-06    .0004147
                _cons |   76.07849   2.073331    36.69   0.000     71.96879    80.18819
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,782
Absorbing 1 HDFE group                            F(  10,    108) =     125.51
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7124
                                                  Adj R-squared   =     0.7080
                                                  Within R-sq.    =     0.3450
Number of clusters (province_id) =        109     Root MSE        =     4.6898

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2001577   .0760976     2.63   0.010     .0493191    .3509963
             m5s_c_13 |    .246038   .0514491     4.78   0.000     .1440569    .3480191
              pd_c_13 |  -.5134561   .0335323   -15.31   0.000     -.579923   -.4469892
           turnout_13 |   .0039732   .0358283     0.11   0.912    -.0670448    .0749911
               income |  -.0004789   .0000942    -5.09   0.000    -.0006656   -.0002922
         unemployment |   .1782317   .0271656     6.56   0.000     .1243848    .2320787
           university |  -.2578965   .0576613    -4.47   0.000    -.3721912   -.1436018
               no_edu |  -.1830586   .0227606    -8.04   0.000     -.228174   -.1379433
           foreigners |  -.0237048   .0365328    -0.65   0.518    -.0961191    .0487095
       pop_density_16 |   .0002182   .0001023     2.13   0.035     .0000155     .000421
                _cons |   76.23081   2.064952    36.92   0.000     72.13772     80.3239
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,720
Absorbing 1 HDFE group                            F(  10,    108) =     124.86
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7158
                                                  Adj R-squared   =     0.7114
                                                  Within R-sq.    =     0.3459
Number of clusters (province_id) =        109     Root MSE        =     4.6624

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2122085    .075782     2.80   0.006     .0619955    .3624216
             m5s_c_13 |   .2382159   .0520354     4.58   0.000     .1350727     .341359
              pd_c_13 |  -.5172519    .033957   -15.23   0.000    -.5845606   -.4499432
           turnout_13 |   .0079934   .0362331     0.22   0.826    -.0638269    .0798137
               income |  -.0004668   .0000934    -5.00   0.000     -.000652   -.0002816
         unemployment |    .181793   .0275093     6.61   0.000     .1272647    .2363212
           university |  -.2667319    .057578    -4.63   0.000    -.3808615   -.1526023
               no_edu |  -.1768925   .0229054    -7.72   0.000     -.222295   -.1314901
           foreigners |  -.0230848   .0367194    -0.63   0.531    -.0958691    .0496994
       pop_density_16 |   .0002361   .0001004     2.35   0.021     .0000371    .0004351
                _cons |   75.86842   2.036062    37.26   0.000     71.83259    79.90425
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,781
Absorbing 1 HDFE group                            F(  10,    108) =     126.01
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7106
                                                  Adj R-squared   =     0.7061
                                                  Within R-sq.    =     0.3450
Number of clusters (province_id) =        109     Root MSE        =     4.6910

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2086508   .0762836     2.74   0.007     .0574434    .3598581
             m5s_c_13 |   .2475092   .0513879     4.82   0.000     .1456494     .349369
              pd_c_13 |  -.5127563   .0335308   -15.29   0.000    -.5792201   -.4462925
           turnout_13 |   .0034702   .0357131     0.10   0.923    -.0673194    .0742598
               income |  -.0004782   .0000943    -5.07   0.000    -.0006651   -.0002914
         unemployment |    .178497   .0272797     6.54   0.000     .1244239      .23257
           university |  -.2572071   .0575857    -4.47   0.000     -.371352   -.1430623
               no_edu |  -.1822171   .0227475    -8.01   0.000    -.2273065   -.1371276
           foreigners |  -.0240279    .036486    -0.66   0.512    -.0963496    .0482937
       pop_density_16 |   .0002149   .0001025     2.10   0.038     .0000118     .000418
                _cons |   76.16596   2.060266    36.97   0.000     72.08216    80.24977
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,700
Absorbing 1 HDFE group                            F(  10,    108) =     140.87
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7094
                                                  Adj R-squared   =     0.7049
                                                  Within R-sq.    =     0.3422
Number of clusters (province_id) =        109     Root MSE        =     4.6860

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |      .1913   .0768628     2.49   0.014     .0389447    .3436554
             m5s_c_13 |   .2550992   .0511096     4.99   0.000     .1537911    .3564072
              pd_c_13 |  -.5098889    .033544   -15.20   0.000     -.576379   -.4433989
           turnout_13 |     .00149    .036096     0.04   0.967    -.0700585    .0730386
               income |  -.0004777   .0000945    -5.05   0.000     -.000665   -.0002903
         unemployment |   .1703946   .0263226     6.47   0.000     .1182186    .2225707
           university |   -.249794    .057407    -4.35   0.000    -.3635845   -.1360035
               no_edu |  -.1761322   .0220878    -7.97   0.000    -.2199141   -.1323503
           foreigners |  -.0247779   .0366917    -0.68   0.501    -.0975073    .0479515
       pop_density_16 |   .0001743   .0001075     1.62   0.108    -.0000388    .0003874
                _cons |   75.93225   2.076865    36.56   0.000     71.81554    80.04896
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,746
Absorbing 1 HDFE group                            F(  10,    108) =     124.73
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7095
                                                  Adj R-squared   =     0.7050
                                                  Within R-sq.    =     0.3443
Number of clusters (province_id) =        109     Root MSE        =     4.6868

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |    .179183   .0716654     2.50   0.014     .0371298    .3212362
             m5s_c_13 |   .2479882   .0515872     4.81   0.000     .1457335    .3502429
              pd_c_13 |  -.5113773   .0335401   -15.25   0.000    -.5778597    -.444895
           turnout_13 |   .0019308   .0358818     0.05   0.957    -.0691932    .0730549
               income |   -.000484   .0000941    -5.14   0.000    -.0006705   -.0002974
         unemployment |   .1764159   .0273611     6.45   0.000     .1221814    .2306503
           university |  -.2573034   .0581406    -4.43   0.000    -.3725482   -.1420586
               no_edu |  -.1809963   .0227871    -7.94   0.000    -.2261642   -.1358284
           foreigners |  -.0221088   .0365149    -0.61   0.546    -.0944876      .05027
       pop_density_16 |   .0002274   .0001043     2.18   0.031     .0000207    .0004342
                _cons |   76.29094   2.065988    36.93   0.000      72.1958    80.38609
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,724
Absorbing 1 HDFE group                            F(  10,    108) =     124.71
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7146
                                                  Adj R-squared   =     0.7102
                                                  Within R-sq.    =     0.3460
Number of clusters (province_id) =        109     Root MSE        =     4.6841

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2106972   .0763282     2.76   0.007     .0594014     .361993
             m5s_c_13 |   .2453463    .051837     4.73   0.000     .1425963    .3480963
              pd_c_13 |  -.5135213   .0337169   -15.23   0.000    -.5803539   -.4466886
           turnout_13 |   .0053003   .0360869     0.15   0.884    -.0662301    .0768308
               income |  -.0004735   .0000942    -5.03   0.000    -.0006602   -.0002868
         unemployment |   .1738157   .0271617     6.40   0.000     .1199766    .2276548
           university |  -.2706558   .0566969    -4.77   0.000    -.3830389   -.1582727
               no_edu |  -.1824705   .0229778    -7.94   0.000    -.2280165   -.1369245
           foreigners |  -.0233838   .0367481    -0.64   0.526    -.0962249    .0494573
       pop_density_16 |   .0002249   .0001023     2.20   0.030     .0000221    .0004277
                _cons |   76.20144   2.081745    36.60   0.000     72.07506    80.32782
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,701
Absorbing 1 HDFE group                            F(  10,    108) =     120.34
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7151
                                                  Adj R-squared   =     0.7107
                                                  Within R-sq.    =     0.3428
Number of clusters (province_id) =        109     Root MSE        =     4.6769

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2080642   .0765942     2.72   0.008     .0562411    .3598872
             m5s_c_13 |   .2453074   .0520971     4.71   0.000     .1420418    .3485729
              pd_c_13 |  -.5128436   .0340345   -15.07   0.000     -.580306   -.4453812
           turnout_13 |   .0008269   .0359105     0.02   0.982    -.0703539    .0720077
               income |   -.000476   .0000948    -5.02   0.000    -.0006638   -.0002881
         unemployment |   .1749087    .027039     6.47   0.000     .1213127    .2285047
           university |  -.2622564   .0581709    -4.51   0.000    -.3775612   -.1469516
               no_edu |   -.182791   .0240074    -7.61   0.000    -.2303778   -.1352042
           foreigners |  -.0243307   .0368203    -0.66   0.510     -.097315    .0486536
       pop_density_16 |   .0002231   .0001022     2.18   0.031     .0000205    .0004257
                _cons |   76.46536   2.083484    36.70   0.000     72.33553    80.59518
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,658
Absorbing 1 HDFE group                            F(  10,    108) =     126.15
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7161
                                                  Adj R-squared   =     0.7117
                                                  Within R-sq.    =     0.3445
Number of clusters (province_id) =        109     Root MSE        =     4.6801

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .1830178   .0730379     2.51   0.014     .0382441    .3277915
             m5s_c_13 |   .2552196   .0511478     4.99   0.000     .1538358    .3566034
              pd_c_13 |  -.5048861   .0328875   -15.35   0.000    -.5700748   -.4396973
           turnout_13 |  -.0035973    .035594    -0.10   0.920    -.0741507    .0669562
               income |  -.0004199    .000086    -4.88   0.000    -.0005905   -.0002493
         unemployment |    .181903   .0271931     6.69   0.000     .1280016    .2358045
           university |  -.2674677   .0582569    -4.59   0.000    -.3829429   -.1519924
               no_edu |    -.18871   .0224044    -8.42   0.000    -.2331194   -.1443007
           foreigners |  -.0170199   .0369307    -0.46   0.646    -.0902229    .0561832
       pop_density_16 |   .0002494   .0000972     2.56   0.012     .0000566    .0004421
                _cons |   75.90448   2.098873    36.16   0.000     71.74415     80.0648
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,649
Absorbing 1 HDFE group                            F(  10,    108) =     119.10
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7176
                                                  Adj R-squared   =     0.7131
                                                  Within R-sq.    =     0.3447
Number of clusters (province_id) =        109     Root MSE        =     4.6514

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2316915   .0750576     3.09   0.003     .0829143    .3804687
             m5s_c_13 |   .2485903   .0532248     4.67   0.000     .1430894    .3540912
              pd_c_13 |   -.512318   .0343063   -14.93   0.000    -.5803189    -.444317
           turnout_13 |   .0011356   .0368051     0.03   0.975    -.0718185    .0740897
               income |  -.0004562   .0000922    -4.95   0.000    -.0006389   -.0002734
         unemployment |   .1835885   .0285288     6.44   0.000     .1270395    .2401375
           university |  -.2738572   .0565298    -4.84   0.000    -.3859091   -.1618054
               no_edu |  -.1762445   .0223399    -7.89   0.000    -.2205262   -.1319629
           foreigners |  -.0233871   .0368099    -0.64   0.527    -.0963507    .0495764
       pop_density_16 |   .0002097   .0001031     2.03   0.044     5.38e-06    .0004141
                _cons |   75.93428   2.097727    36.20   0.000     71.77623    80.09234
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,689
Absorbing 1 HDFE group                            F(  10,    108) =     124.31
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7138
                                                  Adj R-squared   =     0.7093
                                                  Within R-sq.    =     0.3448
Number of clusters (province_id) =        109     Root MSE        =     4.7029

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2073364   .0764481     2.71   0.008      .055803    .3588697
             m5s_c_13 |   .2486588   .0516972     4.81   0.000     .1461859    .3511317
              pd_c_13 |  -.5125065     .03395   -15.10   0.000    -.5798013   -.4452117
           turnout_13 |   .0019759   .0360079     0.05   0.956     -.069398    .0733499
               income |  -.0004805   .0000947    -5.07   0.000    -.0006683   -.0002927
         unemployment |   .1784534   .0273129     6.53   0.000     .1243146    .2325923
           university |  -.2566372   .0581021    -4.42   0.000    -.3718056   -.1414688
               no_edu |  -.1828857   .0231065    -7.91   0.000    -.2286869   -.1370846
           foreigners |  -.0244373   .0373798    -0.65   0.515    -.0985307     .049656
       pop_density_16 |   .0002158   .0001026     2.10   0.038     .0000125    .0004191
                _cons |   76.30633   2.068279    36.89   0.000     72.20665    80.40602
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,777
Absorbing 1 HDFE group                            F(  10,    108) =     124.45
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7134
                                                  Adj R-squared   =     0.7090
                                                  Within R-sq.    =     0.3440
Number of clusters (province_id) =        109     Root MSE        =     4.6822

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2029538   .0760164     2.67   0.009     .0522762    .3536315
             m5s_c_13 |   .2482477   .0514105     4.83   0.000     .1463432    .3501521
              pd_c_13 |  -.5138104     .03357   -15.31   0.000    -.5803519   -.4472689
           turnout_13 |   .0058075   .0357747     0.16   0.871    -.0651043    .0767192
               income |    -.00048   .0000942    -5.10   0.000    -.0006667   -.0002933
         unemployment |   .1786276   .0275959     6.47   0.000     .1239278    .2333274
           university |  -.2528653    .057342    -4.41   0.000    -.3665271   -.1392035
               no_edu |  -.1785791   .0225098    -7.93   0.000    -.2231973   -.1339608
           foreigners |  -.0244221    .036506    -0.67   0.505    -.0967832    .0479391
       pop_density_16 |   .0002195   .0001026     2.14   0.035     .0000162    .0004228
                _cons |   75.89268   2.043287    37.14   0.000     71.84253    79.94283
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,571
Absorbing 1 HDFE group                            F(  10,    108) =     144.66
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7202
                                                  Adj R-squared   =     0.7158
                                                  Within R-sq.    =     0.3553
Number of clusters (province_id) =        109     Root MSE        =     4.6555

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .1894589   .0750579     2.52   0.013     .0406813    .3382366
             m5s_c_13 |   .2566766   .0518281     4.95   0.000     .1539442     .359409
              pd_c_13 |  -.5184999    .034314   -15.11   0.000    -.5865161   -.4504837
           turnout_13 |   .0123191   .0364579     0.34   0.736    -.0599468     .084585
               income |  -.0004564   .0000963    -4.74   0.000    -.0006472   -.0002655
         unemployment |   .1734315   .0269834     6.43   0.000     .1199457    .2269172
           university |  -.2711788   .0578693    -4.69   0.000    -.3858857   -.1564719
               no_edu |  -.1913445   .0221843    -8.63   0.000    -.2353178   -.1473713
           foreigners |  -.0174096   .0378242    -0.46   0.646    -.0923837    .0575645
       pop_density_16 |   .0002017    .000104     1.94   0.055    -4.40e-06    .0004078
                _cons |   75.76005   2.042976    37.08   0.000     71.71051    79.80958
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,784
Absorbing 1 HDFE group                            F(  10,    108) =     126.27
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7130
                                                  Adj R-squared   =     0.7086
                                                  Within R-sq.    =     0.3461
Number of clusters (province_id) =        109     Root MSE        =     4.6873

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .1969471    .075817     2.60   0.011     .0466646    .3472295
             m5s_c_13 |   .2482217    .051436     4.83   0.000     .1462666    .3501768
              pd_c_13 |  -.5153851   .0335245   -15.37   0.000    -.5818365   -.4489336
           turnout_13 |   .0039952   .0357645     0.11   0.911    -.0668962    .0748867
               income |  -.0004779   .0000941    -5.08   0.000    -.0006644   -.0002914
         unemployment |   .1775537   .0273368     6.50   0.000     .1233674    .2317399
           university |  -.2571834   .0575639    -4.47   0.000     -.371285   -.1430819
               no_edu |  -.1815164   .0227168    -7.99   0.000    -.2265451   -.1364877
           foreigners |  -.0234348   .0364977    -0.64   0.522    -.0957796      .04891
       pop_density_16 |   .0002208   .0001021     2.16   0.033     .0000184    .0004232
                _cons |   76.16516   2.060705    36.96   0.000     72.08048    80.24983
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,764
Absorbing 1 HDFE group                            F(  10,    108) =     126.05
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7129
                                                  Adj R-squared   =     0.7085
                                                  Within R-sq.    =     0.3452
Number of clusters (province_id) =        109     Root MSE        =     4.6948

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2066846   .0761771     2.71   0.008     .0556883    .3576809
             m5s_c_13 |   .2472781   .0514075     4.81   0.000     .1453795    .3491767
              pd_c_13 |  -.5127902   .0335511   -15.28   0.000    -.5792942   -.4462861
           turnout_13 |    .003127   .0357322     0.09   0.930    -.0677004    .0739545
               income |  -.0004772   .0000945    -5.05   0.000    -.0006645     -.00029
         unemployment |   .1784661   .0272118     6.56   0.000     .1245275    .2324046
           university |  -.2597504   .0578153    -4.49   0.000    -.3743503   -.1451505
               no_edu |  -.1826535    .022849    -7.99   0.000    -.2279441   -.1373629
           foreigners |  -.0240954   .0366743    -0.66   0.513    -.0967902    .0485995
       pop_density_16 |   .0002166   .0001025     2.11   0.037     .0000134    .0004198
                _cons |    76.2522    2.06444    36.94   0.000     72.16012    80.34428
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,781
Absorbing 1 HDFE group                            F(  10,    108) =     124.97
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7123
                                                  Adj R-squared   =     0.7079
                                                  Within R-sq.    =     0.3439
Number of clusters (province_id) =        109     Root MSE        =     4.6928

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2083952   .0762331     2.73   0.007      .057288    .3595024
             m5s_c_13 |   .2459664   .0513546     4.79   0.000     .1441727    .3477601
              pd_c_13 |  -.5128216   .0335858   -15.27   0.000    -.5793944   -.4462487
           turnout_13 |   .0033558   .0357152     0.09   0.925     -.067438    .0741495
               income |  -.0004732   .0000945    -5.01   0.000    -.0006605   -.0002859
         unemployment |   .1785446   .0271378     6.58   0.000     .1247527    .2323365
           university |  -.2593419   .0576924    -4.50   0.000    -.3736983   -.1449855
               no_edu |  -.1831262   .0227709    -8.04   0.000     -.228262   -.1379903
           foreigners |  -.0226395   .0365475    -0.62   0.537     -.095083    .0498039
       pop_density_16 |   .0002138   .0001026     2.08   0.040     .0000104    .0004173
                _cons |   76.20017   2.057993    37.03   0.000     72.12087    80.27947
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,764
Absorbing 1 HDFE group                            F(  10,    108) =     124.98
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7057
                                                  Adj R-squared   =     0.7011
                                                  Within R-sq.    =     0.3449
Number of clusters (province_id) =        109     Root MSE        =     4.6979

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .1991952   .0767597     2.60   0.011     .0470442    .3513462
             m5s_c_13 |   .2473117   .0513347     4.82   0.000     .1455575    .3490659
              pd_c_13 |  -.5141265   .0335442   -15.33   0.000     -.580617    -.447636
           turnout_13 |   .0033526   .0357009     0.09   0.925    -.0674129     .074118
               income |  -.0004797   .0000942    -5.09   0.000    -.0006664   -.0002929
         unemployment |   .1777504   .0271164     6.56   0.000      .124001    .2314998
           university |  -.2576831   .0578437    -4.45   0.000    -.3723394   -.1430268
               no_edu |  -.1823041   .0227517    -8.01   0.000     -.227402   -.1372062
           foreigners |  -.0236444   .0366718    -0.64   0.520    -.0963342    .0490454
       pop_density_16 |   .0002101   .0001034     2.03   0.045     5.20e-06     .000415
                _cons |   76.29555   2.059492    37.05   0.000     72.21328    80.37782
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,743
Absorbing 1 HDFE group                            F(  10,    108) =     125.42
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7141
                                                  Adj R-squared   =     0.7097
                                                  Within R-sq.    =     0.3454
Number of clusters (province_id) =        109     Root MSE        =     4.6853

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2258726   .0757595     2.98   0.004     .0757041    .3760412
             m5s_c_13 |   .2467678   .0520326     4.74   0.000     .1436302    .3499053
              pd_c_13 |  -.5116858   .0337753   -15.15   0.000    -.5786344   -.4447373
           turnout_13 |   .0021826   .0364208     0.06   0.952    -.0700097    .0743749
               income |  -.0004811   .0000945    -5.09   0.000    -.0006684   -.0002938
         unemployment |   .1804604   .0275944     6.54   0.000     .1257636    .2351572
           university |  -.2590293   .0580328    -4.46   0.000    -.3740604   -.1439983
               no_edu |   -.183206   .0230761    -7.94   0.000    -.2289468   -.1374652
           foreigners |  -.0233365   .0368049    -0.63   0.527    -.0962902    .0496173
       pop_density_16 |   .0002089   .0001025     2.04   0.044     5.85e-06     .000412
                _cons |   76.34325   2.079241    36.72   0.000     72.22183    80.46467
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,774
Absorbing 1 HDFE group                            F(  10,    108) =     125.53
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7110
                                                  Adj R-squared   =     0.7066
                                                  Within R-sq.    =     0.3446
Number of clusters (province_id) =        109     Root MSE        =     4.6943

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2055406    .076079     2.70   0.008     .0547388    .3563424
             m5s_c_13 |   .2460225   .0515668     4.77   0.000     .1438082    .3482368
              pd_c_13 |  -.5141534   .0335419   -15.33   0.000    -.5806392   -.4476676
           turnout_13 |   .0036182   .0357357     0.10   0.920    -.0672163    .0744526
               income |  -.0004783   .0000941    -5.08   0.000    -.0006649   -.0002916
         unemployment |   .1781027   .0271298     6.56   0.000     .1243268    .2318786
           university |  -.2584188   .0576378    -4.48   0.000     -.372667   -.1441706
               no_edu |   -.182813   .0227367    -8.04   0.000    -.2278811   -.1377449
           foreigners |  -.0248556   .0366435    -0.68   0.499    -.0974893    .0477781
       pop_density_16 |   .0002197    .000102     2.15   0.033     .0000176    .0004219
                _cons |   76.29125   2.059712    37.04   0.000     72.20854    80.37396
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,713
Absorbing 1 HDFE group                            F(  10,    108) =     127.21
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7119
                                                  Adj R-squared   =     0.7074
                                                  Within R-sq.    =     0.3463
Number of clusters (province_id) =        109     Root MSE        =     4.6948

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2306852    .076991     3.00   0.003     .0780757    .3832947
             m5s_c_13 |   .2464637     .05171     4.77   0.000     .1439655    .3489619
              pd_c_13 |   -.513517   .0338577   -15.17   0.000    -.5806288   -.4464052
           turnout_13 |   .0026606   .0359706     0.07   0.941    -.0686394    .0739606
               income |  -.0004805    .000095    -5.06   0.000    -.0006687   -.0002922
         unemployment |   .1751264   .0271953     6.44   0.000     .1212205    .2290323
           university |  -.2630689   .0582942    -4.51   0.000    -.3786182   -.1475197
               no_edu |  -.1849658   .0229329    -8.07   0.000    -.2304228   -.1395088
           foreigners |  -.0235306     .03665    -0.64   0.522    -.0961773    .0491161
       pop_density_16 |   .0002165   .0001025     2.11   0.037     .0000133    .0004196
                _cons |   76.40784   2.060821    37.08   0.000     72.32293    80.49274
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,744
Absorbing 1 HDFE group                            F(  10,    108) =     124.83
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7131
                                                  Adj R-squared   =     0.7086
                                                  Within R-sq.    =     0.3441
Number of clusters (province_id) =        109     Root MSE        =     4.6968

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2167153   .0771708     2.81   0.006     .0637494    .3696811
             m5s_c_13 |   .2425228   .0516983     4.69   0.000     .1400479    .3449977
              pd_c_13 |  -.5152032   .0338101   -15.24   0.000    -.5822206   -.4481858
           turnout_13 |   .0047992   .0359099     0.13   0.894    -.0663805     .075979
               income |  -.0004874   .0000944    -5.16   0.000    -.0006745   -.0003003
         unemployment |   .1777068   .0271163     6.55   0.000     .1239576     .231456
           university |   -.250072   .0575979    -4.34   0.000     -.364241    -.135903
               no_edu |  -.1826713   .0227764    -8.02   0.000    -.2278181   -.1375244
           foreigners |  -.0227044   .0365581    -0.62   0.536    -.0951689      .04976
       pop_density_16 |   .0002264   .0001021     2.22   0.029     .0000241    .0004287
                _cons |   76.28226   2.069108    36.87   0.000     72.18093    80.38359
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,779
Absorbing 1 HDFE group                            F(  10,    108) =     125.81
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7128
                                                  Adj R-squared   =     0.7084
                                                  Within R-sq.    =     0.3449
Number of clusters (province_id) =        109     Root MSE        =     4.6933

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2081601   .0764386     2.72   0.008     .0566456    .3596746
             m5s_c_13 |   .2464583   .0513427     4.80   0.000     .1446883    .3482284
              pd_c_13 |  -.5137617   .0336301   -15.28   0.000    -.5804224    -.447101
           turnout_13 |   .0031103   .0357187     0.09   0.931    -.0676902    .0739109
               income |  -.0004765   .0000942    -5.06   0.000    -.0006633   -.0002898
         unemployment |    .178395   .0271395     6.57   0.000     .1245999    .2321901
           university |  -.2583377   .0576753    -4.48   0.000    -.3726601   -.1440153
               no_edu |  -.1829941   .0227342    -8.05   0.000    -.2280572   -.1379311
           foreigners |  -.0232869   .0365767    -0.64   0.526    -.0957883    .0492145
       pop_density_16 |    .000216   .0001024     2.11   0.037      .000013    .0004189
                _cons |   76.25421   2.056896    37.07   0.000     72.17708    80.33133
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,776
Absorbing 1 HDFE group                            F(  10,    108) =     125.66
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7116
                                                  Adj R-squared   =     0.7071
                                                  Within R-sq.    =     0.3443
Number of clusters (province_id) =        109     Root MSE        =     4.6949

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2065961   .0762417     2.71   0.008     .0554718    .3577203
             m5s_c_13 |   .2468348   .0513078     4.81   0.000     .1451338    .3485359
              pd_c_13 |  -.5130128   .0335844   -15.28   0.000     -.579583   -.4464426
           turnout_13 |   .0038862   .0357257     0.11   0.914    -.0669283    .0747006
               income |  -.0004799   .0000943    -5.09   0.000    -.0006668    -.000293
         unemployment |   .1777118   .0271198     6.55   0.000     .1239556     .231468
           university |  -.2572763   .0576463    -4.46   0.000    -.3715413   -.1430112
               no_edu |  -.1818563   .0227814    -7.98   0.000    -.2270129   -.1366996
           foreigners |  -.0231666   .0367938    -0.63   0.530    -.0960983    .0497651
       pop_density_16 |   .0002178   .0001025     2.12   0.036     .0000146     .000421
                _cons |   76.20239   2.060805    36.98   0.000     72.11752    80.28726
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,739
Absorbing 1 HDFE group                            F(  10,    108) =     124.11
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7145
                                                  Adj R-squared   =     0.7100
                                                  Within R-sq.    =     0.3458
Number of clusters (province_id) =        109     Root MSE        =     4.6797

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2026827   .0765616     2.65   0.009     .0509243     .354441
             m5s_c_13 |   .2447097   .0515938     4.74   0.000     .1424418    .3469777
              pd_c_13 |  -.5115433   .0335275   -15.26   0.000    -.5780005   -.4450861
           turnout_13 |   .0009164   .0358473     0.03   0.980    -.0701391    .0719719
               income |  -.0004798   .0000955    -5.02   0.000    -.0006691   -.0002904
         unemployment |   .1746444   .0267877     6.52   0.000     .1215465    .2277424
           university |  -.2575511   .0584978    -4.40   0.000    -.3735039   -.1415983
               no_edu |  -.1855549   .0227774    -8.15   0.000    -.2307036   -.1404061
           foreigners |  -.0153766   .0360284    -0.43   0.670    -.0867911    .0560379
       pop_density_16 |   .0002095   .0001043     2.01   0.047     2.89e-06    .0004162
                _cons |   76.53815   2.059586    37.16   0.000     72.45569     80.6206
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,752
Absorbing 1 HDFE group                            F(  10,    108) =     124.36
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7161
                                                  Adj R-squared   =     0.7118
                                                  Within R-sq.    =     0.3476
Number of clusters (province_id) =        109     Root MSE        =     4.6605

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .1977741    .075553     2.62   0.010     .0480149    .3475333
             m5s_c_13 |   .2436798   .0519675     4.69   0.000     .1406711    .3466884
              pd_c_13 |  -.5168645   .0337702   -15.31   0.000    -.5838028   -.4499262
           turnout_13 |   .0035031   .0362935     0.10   0.923     -.068437    .0754431
               income |  -.0004705   .0000941    -5.00   0.000    -.0006569   -.0002841
         unemployment |   .1758352    .027162     6.47   0.000     .1219954     .229675
           university |   -.263747   .0578685    -4.56   0.000    -.3784524   -.1490415
               no_edu |   -.181873   .0231526    -7.86   0.000    -.2277655   -.1359805
           foreigners |  -.0218378   .0365403    -0.60   0.551     -.094267    .0505913
       pop_density_16 |   .0002285   .0001016     2.25   0.027     .0000271      .00043
                _cons |   76.29932   2.079166    36.70   0.000     72.17805    80.42058
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,697
Absorbing 1 HDFE group                            F(  10,    108) =     124.89
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7163
                                                  Adj R-squared   =     0.7119
                                                  Within R-sq.    =     0.3460
Number of clusters (province_id) =        109     Root MSE        =     4.6673

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2056308   .0767948     2.68   0.009     .0534101    .3578515
             m5s_c_13 |   .2523229   .0516686     4.88   0.000     .1499069     .354739
              pd_c_13 |  -.5072713   .0333559   -15.21   0.000    -.5733886    -.441154
           turnout_13 |  -.0017957   .0357598    -0.05   0.960    -.0726778    .0690864
               income |  -.0004812   .0000968    -4.97   0.000    -.0006731   -.0002894
         unemployment |   .1836569   .0273915     6.70   0.000     .1293623    .2379515
           university |  -.2619654   .0594216    -4.41   0.000    -.3797494   -.1441815
               no_edu |  -.1819566   .0239605    -7.59   0.000    -.2294504   -.1344628
           foreigners |  -.0218418   .0374933    -0.58   0.561      -.09616    .0524764
       pop_density_16 |   .0002081    .000102     2.04   0.044     5.91e-06    .0004104
                _cons |   76.36603   2.088913    36.56   0.000     72.22544    80.50662
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,772
Absorbing 1 HDFE group                            F(  10,    108) =     126.46
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7130
                                                  Adj R-squared   =     0.7086
                                                  Within R-sq.    =     0.3453
Number of clusters (province_id) =        109     Root MSE        =     4.6930

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2060059   .0761586     2.70   0.008     .0550463    .3569654
             m5s_c_13 |   .2467813   .0513049     4.81   0.000     .1450862    .3484764
              pd_c_13 |  -.5133932    .033549   -15.30   0.000    -.5798932   -.4468932
           turnout_13 |   .0035413   .0357348     0.10   0.921    -.0672914    .0743739
               income |  -.0004801   .0000944    -5.09   0.000    -.0006673    -.000293
         unemployment |   .1792274   .0271559     6.60   0.000     .1253997     .233055
           university |  -.2572248   .0578864    -4.44   0.000    -.3719657   -.1424839
               no_edu |  -.1828974    .022792    -8.02   0.000    -.2280752   -.1377197
           foreigners |  -.0237194   .0365122    -0.65   0.517    -.0960928    .0486541
       pop_density_16 |   .0002198    .000102     2.15   0.033     .0000176     .000422
                _cons |   76.23357   2.061825    36.97   0.000     72.14668    80.32046
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,771
Absorbing 1 HDFE group                            F(  10,    108) =     124.82
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7126
                                                  Adj R-squared   =     0.7082
                                                  Within R-sq.    =     0.3442
Number of clusters (province_id) =        109     Root MSE        =     4.6884

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .1977246   .0762562     2.59   0.011     .0465715    .3488777
             m5s_c_13 |   .2454653   .0514998     4.77   0.000     .1433838    .3475468
              pd_c_13 |  -.5112117   .0335902   -15.22   0.000    -.5777933   -.4446302
           turnout_13 |  -.0001289   .0357156    -0.00   0.997    -.0709235    .0706657
               income |  -.0004773   .0000946    -5.05   0.000    -.0006647   -.0002899
         unemployment |   .1775326   .0271803     6.53   0.000     .1236566    .2314087
           university |  -.2583546    .057951    -4.46   0.000    -.3732237   -.1434856
               no_edu |  -.1849531   .0226556    -8.16   0.000    -.2298604   -.1400457
           foreigners |  -.0229554   .0366797    -0.63   0.533     -.095661    .0497501
       pop_density_16 |   .0002177   .0001023     2.13   0.036     .0000149    .0004205
                _cons |   76.54687   2.039337    37.54   0.000     72.50455    80.58919
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,707
Absorbing 1 HDFE group                            F(  10,    108) =     123.97
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7135
                                                  Adj R-squared   =     0.7091
                                                  Within R-sq.    =     0.3454
Number of clusters (province_id) =        109     Root MSE        =     4.6991

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2003914   .0764561     2.62   0.010     .0488422    .3519406
             m5s_c_13 |   .2473603   .0516743     4.79   0.000     .1449328    .3497877
              pd_c_13 |  -.5157052   .0336974   -15.30   0.000    -.5824993   -.4489111
           turnout_13 |   .0058206   .0359758     0.16   0.872    -.0654896    .0771309
               income |  -.0004774   .0000942    -5.07   0.000    -.0006642   -.0002907
         unemployment |   .1770403    .027479     6.44   0.000     .1225722    .2315084
           university |  -.2622277   .0577227    -4.54   0.000     -.376644   -.1478114
               no_edu |  -.1817897   .0228587    -7.95   0.000    -.2270995   -.1364798
           foreigners |  -.0238477    .036599    -0.65   0.516    -.0963932    .0486978
       pop_density_16 |    .000219   .0001025     2.14   0.035     .0000157    .0004222
                _cons |   76.09847    2.07354    36.70   0.000     71.98835    80.20858
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,724
Absorbing 1 HDFE group                            F(  10,    108) =     126.65
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7137
                                                  Adj R-squared   =     0.7092
                                                  Within R-sq.    =     0.3444
Number of clusters (province_id) =        109     Root MSE        =     4.6884

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2127228   .0770763     2.76   0.007     .0599441    .3655014
             m5s_c_13 |   .2492836   .0514931     4.84   0.000     .1472152    .3513519
              pd_c_13 |  -.5102028   .0337046   -15.14   0.000    -.5770111   -.4433945
           turnout_13 |   .0035977   .0358807     0.10   0.920    -.0675241    .0747196
               income |  -.0004691   .0000951    -4.93   0.000    -.0006576   -.0002806
         unemployment |   .1763763   .0270707     6.52   0.000     .1227175    .2300351
           university |  -.2615784   .0578151    -4.52   0.000    -.3761779   -.1469789
               no_edu |  -.1828898   .0229102    -7.98   0.000    -.2283018   -.1374778
           foreigners |   -.023952    .036821    -0.65   0.517    -.0969375    .0490336
       pop_density_16 |   .0002476   .0000966     2.56   0.012      .000056    .0004391
                _cons |   76.06333   2.064275    36.85   0.000     71.97158    80.15508
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,784
Absorbing 1 HDFE group                            F(  10,    108) =     124.91
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7119
                                                  Adj R-squared   =     0.7075
                                                  Within R-sq.    =     0.3444
Number of clusters (province_id) =        109     Root MSE        =     4.6925

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2038339   .0763718     2.67   0.009     .0524518     .355216
             m5s_c_13 |   .2460208   .0513426     4.79   0.000     .1442509    .3477908
              pd_c_13 |  -.5145092   .0336456   -15.29   0.000    -.5812006   -.4478179
           turnout_13 |   .0027308   .0356893     0.08   0.939    -.0680115    .0734731
               income |  -.0004767   .0000941    -5.07   0.000    -.0006632   -.0002903
         unemployment |   .1776058   .0271022     6.55   0.000     .1238845    .2313271
           university |  -.2582225   .0576332    -4.48   0.000    -.3724615   -.1439835
               no_edu |   -.183379   .0227522    -8.06   0.000    -.2284778   -.1382803
           foreigners |  -.0236655   .0365762    -0.65   0.519     -.096166    .0488349
       pop_density_16 |   .0002144   .0001025     2.09   0.039     .0000112    .0004176
                _cons |   76.35513    2.05899    37.08   0.000     72.27385     80.4364
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,743
Absorbing 1 HDFE group                            F(  10,    108) =     124.72
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7134
                                                  Adj R-squared   =     0.7090
                                                  Within R-sq.    =     0.3445
Number of clusters (province_id) =        109     Root MSE        =     4.6931

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2101057    .076695     2.74   0.007      .058083    .3621284
             m5s_c_13 |   .2428933   .0515691     4.71   0.000     .1406743    .3451123
              pd_c_13 |   -.513296   .0337126   -15.23   0.000    -.5801202   -.4464719
           turnout_13 |   .0041101   .0358844     0.11   0.909     -.067019    .0752391
               income |  -.0004734   .0000944    -5.01   0.000    -.0006605   -.0002863
         unemployment |   .1767413   .0270277     6.54   0.000     .1231678    .2303148
           university |  -.2621968   .0577428    -4.54   0.000    -.3766529   -.1477406
               no_edu |  -.1847159   .0227574    -8.12   0.000     -.229825   -.1396068
           foreigners |  -.0230864   .0367472    -0.63   0.531    -.0959258    .0497531
       pop_density_16 |   .0002199   .0001025     2.14   0.034     .0000166    .0004232
                _cons |    76.3025   2.057149    37.09   0.000     72.22488    80.38013
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,773
Absorbing 1 HDFE group                            F(  10,    108) =     125.11
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7115
                                                  Adj R-squared   =     0.7070
                                                  Within R-sq.    =     0.3441
Number of clusters (province_id) =        109     Root MSE        =     4.6946

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2068734   .0761703     2.72   0.008     .0558906    .3578561
             m5s_c_13 |   .2464236   .0514533     4.79   0.000     .1444342     .348413
              pd_c_13 |  -.5129148    .033556   -15.29   0.000    -.5794286    -.446401
           turnout_13 |    .003603   .0357764     0.10   0.920    -.0673121    .0745181
               income |  -.0004816   .0000944    -5.10   0.000    -.0006686   -.0002945
         unemployment |   .1772551   .0271032     6.54   0.000     .1235319    .2309783
           university |  -.2578141   .0577378    -4.47   0.000    -.3722604   -.1433678
               no_edu |  -.1823716   .0227396    -8.02   0.000    -.2274453   -.1372978
           foreigners |  -.0245188   .0366285    -0.67   0.505    -.0971228    .0480852
       pop_density_16 |   .0002176   .0001025     2.12   0.036     .0000143    .0004208
                _cons |   76.29243   2.060189    37.03   0.000     72.20878    80.37608
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,750
Absorbing 1 HDFE group                            F(  10,    108) =     125.08
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7130
                                                  Adj R-squared   =     0.7086
                                                  Within R-sq.    =     0.3453
Number of clusters (province_id) =        109     Root MSE        =     4.6922

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2061628   .0762844     2.70   0.008      .054954    .3573716
             m5s_c_13 |   .2512483   .0514502     4.88   0.000     .1492651    .3532315
              pd_c_13 |  -.5144559   .0336604   -15.28   0.000    -.5811767    -.447735
           turnout_13 |   .0046371   .0357493     0.13   0.897    -.0662243    .0754985
               income |  -.0004771   .0000948    -5.03   0.000    -.0006651   -.0002891
         unemployment |   .1762536   .0270587     6.51   0.000     .1226186    .2298885
           university |  -.2578177   .0582529    -4.43   0.000    -.3732851   -.1423503
               no_edu |  -.1790874   .0226101    -7.92   0.000    -.2239046   -.1342702
           foreigners |  -.0188839   .0365205    -0.52   0.606    -.0912738    .0535061
       pop_density_16 |   .0002182    .000103     2.12   0.036      .000014    .0004224
                _cons |   75.96817   2.051174    37.04   0.000     71.90238    80.03395
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,736
Absorbing 1 HDFE group                            F(  10,    108) =     124.78
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7121
                                                  Adj R-squared   =     0.7076
                                                  Within R-sq.    =     0.3439
Number of clusters (province_id) =        109     Root MSE        =     4.7018

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2111904   .0762567     2.77   0.007     .0600365    .3623444
             m5s_c_13 |   .2459262   .0515334     4.77   0.000     .1437782    .3480743
              pd_c_13 |  -.5139883   .0340022   -15.12   0.000    -.5813866   -.4465901
           turnout_13 |   .0036161   .0358848     0.10   0.920    -.0675137     .074746
               income |  -.0004802   .0000943    -5.09   0.000    -.0006671   -.0002932
         unemployment |   .1783788   .0271944     6.56   0.000     .1244748    .2322829
           university |  -.2576773   .0578349    -4.46   0.000    -.3723162   -.1430384
               no_edu |  -.1830301   .0227912    -8.03   0.000    -.2282062   -.1378541
           foreigners |  -.0232519   .0367563    -0.63   0.528    -.0961094    .0496055
       pop_density_16 |   .0002175   .0001023     2.13   0.036     .0000146    .0004203
                _cons |    76.2885     2.0569    37.09   0.000     72.21136    80.36563
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,787
Absorbing 1 HDFE group                            F(  10,    108) =     126.23
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7126
                                                  Adj R-squared   =     0.7082
                                                  Within R-sq.    =     0.3450
Number of clusters (province_id) =        109     Root MSE        =     4.6925

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2088097   .0764274     2.73   0.007     .0573173    .3603021
             m5s_c_13 |   .2468362   .0513264     4.81   0.000     .1450984    .3485741
              pd_c_13 |  -.5131117   .0334978   -15.32   0.000    -.5795103   -.4467132
           turnout_13 |   .0031549   .0357471     0.09   0.930    -.0677022    .0740119
               income |  -.0004791   .0000941    -5.09   0.000    -.0006657   -.0002926
         unemployment |    .178092   .0271153     6.57   0.000     .1243448    .2318391
           university |  -.2573409   .0575982    -4.47   0.000    -.3715106   -.1431712
               no_edu |  -.1827594   .0227809    -8.02   0.000    -.2279151   -.1376036
           foreigners |  -.0239813   .0365162    -0.66   0.513    -.0963627    .0484001
       pop_density_16 |   .0002174   .0001023     2.13   0.036     .0000148    .0004201
                _cons |   76.26551   2.058382    37.05   0.000     72.18544    80.34557
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,773
Absorbing 1 HDFE group                            F(  10,    108) =     125.27
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7128
                                                  Adj R-squared   =     0.7083
                                                  Within R-sq.    =     0.3447
Number of clusters (province_id) =        109     Root MSE        =     4.6894

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2076043    .076197     2.72   0.008     .0565687    .3586399
             m5s_c_13 |   .2463742    .051573     4.78   0.000     .1441476    .3486009
              pd_c_13 |  -.5131596   .0335722   -15.29   0.000    -.5797055   -.4466136
           turnout_13 |   .0018298    .035811     0.05   0.959    -.0691537    .0728134
               income |  -.0004742   .0000941    -5.04   0.000    -.0006608   -.0002877
         unemployment |   .1770868   .0271155     6.53   0.000     .1233393    .2308344
           university |  -.2625861   .0575897    -4.56   0.000    -.3767389   -.1484333
               no_edu |  -.1835443   .0228171    -8.04   0.000    -.2287717   -.1383168
           foreigners |  -.0240738   .0365469    -0.66   0.511     -.096516    .0483684
       pop_density_16 |   .0002191   .0001022     2.14   0.034     .0000166    .0004216
                _cons |   76.37518   2.061275    37.05   0.000     72.28938    80.46099
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,776
Absorbing 1 HDFE group                            F(  10,    108) =     125.11
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7124
                                                  Adj R-squared   =     0.7080
                                                  Within R-sq.    =     0.3442
Number of clusters (province_id) =        109     Root MSE        =     4.6874

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2057334   .0760124     2.71   0.008     .0550635    .3564032
             m5s_c_13 |   .2445307   .0515066     4.75   0.000     .1424357    .3466257
              pd_c_13 |  -.5127926   .0335319   -15.29   0.000    -.5792587   -.4463265
           turnout_13 |   .0030871    .035755     0.09   0.931    -.0677854    .0739597
               income |  -.0004751   .0000941    -5.05   0.000    -.0006617   -.0002884
         unemployment |    .177966   .0272457     6.53   0.000     .1239604    .2319716
           university |  -.2598129   .0576384    -4.51   0.000    -.3740623   -.1455635
               no_edu |  -.1830712   .0227793    -8.04   0.000    -.2282237   -.1379187
           foreigners |  -.0236922   .0365207    -0.65   0.518    -.0960826    .0486982
       pop_density_16 |   .0002188   .0001024     2.14   0.035     .0000159    .0004218
                _cons |   76.26658   2.061599    36.99   0.000     72.18013    80.35302
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,697
Absorbing 1 HDFE group                            F(  10,    108) =     120.69
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7129
                                                  Adj R-squared   =     0.7084
                                                  Within R-sq.    =     0.3443
Number of clusters (province_id) =        109     Root MSE        =     4.6796

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2015309   .0770291     2.62   0.010     .0488459    .3542159
             m5s_c_13 |   .2473865   .0519317     4.76   0.000     .1444489    .3503241
              pd_c_13 |  -.5148736   .0340285   -15.13   0.000    -.5823239   -.4474234
           turnout_13 |   .0064361   .0363015     0.18   0.860    -.0655199     .078392
               income |  -.0004764   .0000947    -5.03   0.000    -.0006641   -.0002888
         unemployment |   .1791178   .0280353     6.39   0.000     .1235469    .2346887
           university |  -.2613021   .0580949    -4.50   0.000    -.3764564   -.1461479
               no_edu |  -.1804989   .0229743    -7.86   0.000     -.226038   -.1349598
           foreigners |  -.0257207     .03667    -0.70   0.485     -.098407    .0469657
       pop_density_16 |   .0002182   .0001027     2.12   0.036     .0000147    .0004217
                _cons |   75.91176   2.064219    36.78   0.000     71.82012     80.0034
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,670
Absorbing 1 HDFE group                            F(  10,    108) =     126.26
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7116
                                                  Adj R-squared   =     0.7071
                                                  Within R-sq.    =     0.3429
Number of clusters (province_id) =        109     Root MSE        =     4.7228

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2158165   .0785881     2.75   0.007     .0600413    .3715918
             m5s_c_13 |   .2437306    .051693     4.71   0.000     .1412661    .3461951
              pd_c_13 |  -.5147342   .0337494   -15.25   0.000    -.5816313    -.447837
           turnout_13 |    .004515   .0359468     0.13   0.900    -.0667378    .0757677
               income |  -.0004753   .0000953    -4.99   0.000    -.0006641   -.0002864
         unemployment |   .1774218   .0270399     6.56   0.000     .1238241    .2310195
           university |  -.2549222   .0580659    -4.39   0.000    -.3700189   -.1398256
               no_edu |  -.1819171    .022751    -8.00   0.000    -.2270136   -.1368206
           foreigners |  -.0254447   .0371689    -0.68   0.495      -.09912    .0482305
       pop_density_16 |   .0002509    .000114     2.20   0.030     .0000249    .0004769
                _cons |   76.18929   2.064111    36.91   0.000     72.09787    80.28072
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,757
Absorbing 1 HDFE group                            F(  10,    108) =     124.95
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7100
                                                  Adj R-squared   =     0.7055
                                                  Within R-sq.    =     0.3445
Number of clusters (province_id) =        109     Root MSE        =     4.6959

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2065407   .0762639     2.71   0.008     .0553723    .3577091
             m5s_c_13 |   .2460126   .0514891     4.78   0.000     .1439523     .348073
              pd_c_13 |  -.5146544    .033783   -15.23   0.000    -.5816181   -.4476907
           turnout_13 |   .0027959   .0356742     0.08   0.938    -.0679165    .0735083
               income |  -.0004785   .0000946    -5.06   0.000     -.000666   -.0002911
         unemployment |   .1771002   .0270956     6.54   0.000      .123392    .2308084
           university |  -.2570016   .0577802    -4.45   0.000     -.371532   -.1424711
               no_edu |  -.1819207   .0227705    -7.99   0.000    -.2270558   -.1367857
           foreigners |  -.0243956   .0367429    -0.66   0.508    -.0972265    .0484353
       pop_density_16 |   .0002184   .0001024     2.13   0.035     .0000155    .0004213
                _cons |   76.33635   2.066357    36.94   0.000     72.24047    80.43223
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,749
Absorbing 1 HDFE group                            F(  10,    108) =     124.90
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7119
                                                  Adj R-squared   =     0.7074
                                                  Within R-sq.    =     0.3441
Number of clusters (province_id) =        109     Root MSE        =     4.7036

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2115035   .0770681     2.74   0.007     .0587411    .3642659
             m5s_c_13 |   .2461133   .0514456     4.78   0.000     .1441392    .3480874
              pd_c_13 |   -.513549   .0336716   -15.25   0.000    -.5802919    -.446806
           turnout_13 |   .0036038   .0357772     0.10   0.920    -.0673127    .0745204
               income |  -.0004783   .0000945    -5.06   0.000    -.0006656    -.000291
         unemployment |   .1779723   .0271112     6.56   0.000     .1242332    .2317113
           university |  -.2570665   .0577481    -4.45   0.000    -.3715333   -.1425996
               no_edu |  -.1825097   .0227348    -8.03   0.000    -.2275741   -.1374453
           foreigners |  -.0232552   .0366219    -0.64   0.527    -.0958463    .0493358
       pop_density_16 |   .0002173   .0001056     2.06   0.042     7.96e-06    .0004267
                _cons |   76.24426   2.059265    37.02   0.000     72.16244    80.32608
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,712
Absorbing 1 HDFE group                            F(  10,    108) =     120.99
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7083
                                                  Adj R-squared   =     0.7038
                                                  Within R-sq.    =     0.3431
Number of clusters (province_id) =        109     Root MSE        =     4.7046

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |    .205509   .0791143     2.60   0.011     .0486907    .3623272
             m5s_c_13 |   .2460173   .0518908     4.74   0.000     .1431607     .348874
              pd_c_13 |  -.5136927   .0338647   -15.17   0.000    -.5808185   -.4465669
           turnout_13 |   .0031438   .0364567     0.09   0.931    -.0691197    .0754074
               income |   -.000469   .0000943    -4.97   0.000     -.000656    -.000282
         unemployment |   .1742131   .0278503     6.26   0.000      .119009    .2294173
           university |  -.2602094   .0583109    -4.46   0.000    -.3757917   -.1446272
               no_edu |  -.1834177   .0228147    -8.04   0.000    -.2286404   -.1381949
           foreigners |  -.0225689   .0368349    -0.61   0.541    -.0955821    .0504443
       pop_density_16 |   .0001712   .0001437     1.19   0.236    -.0001137    .0004561
                _cons |    76.2181   2.073304    36.76   0.000     72.10845    80.32775
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,716
Absorbing 1 HDFE group                            F(  10,    108) =     124.45
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7132
                                                  Adj R-squared   =     0.7088
                                                  Within R-sq.    =     0.3449
Number of clusters (province_id) =        109     Root MSE        =     4.7006

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2049203   .0765388     2.68   0.009      .053207    .3566336
             m5s_c_13 |   .2466604   .0514731     4.79   0.000     .1446318    .3486891
              pd_c_13 |  -.5133763   .0336497   -15.26   0.000    -.5800758   -.4466767
           turnout_13 |   .0019392   .0357863     0.05   0.957    -.0689954    .0728738
               income |  -.0004756   .0000952    -4.99   0.000    -.0006643   -.0002868
         unemployment |    .178142   .0272182     6.54   0.000     .1241909    .2320931
           university |   -.251652   .0577838    -4.36   0.000    -.3661895   -.1371145
               no_edu |  -.1826622   .0228316    -8.00   0.000    -.2279184   -.1374061
           foreigners |   -.024059   .0368279    -0.65   0.515    -.0970582    .0489402
       pop_density_16 |   .0002146   .0001026     2.09   0.039     .0000113     .000418
                _cons |   76.30222    2.06551    36.94   0.000     72.20802    80.39642
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,752
Absorbing 1 HDFE group                            F(  10,    108) =     124.89
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7127
                                                  Adj R-squared   =     0.7083
                                                  Within R-sq.    =     0.3458
Number of clusters (province_id) =        109     Root MSE        =     4.6783

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |    .203189   .0758315     2.68   0.009     .0528778    .3535002
             m5s_c_13 |   .2435279   .0515982     4.72   0.000     .1412512    .3458046
              pd_c_13 |  -.5138214   .0339372   -15.14   0.000    -.5810909   -.4465519
           turnout_13 |   .0076914   .0360674     0.21   0.832    -.0638004    .0791832
               income |   -.000483   .0000943    -5.12   0.000    -.0006698   -.0002961
         unemployment |   .1799836   .0277714     6.48   0.000     .1249359    .2350313
           university |  -.2576888    .057965    -4.45   0.000    -.3725855   -.1427921
               no_edu |  -.1823995   .0228585    -7.98   0.000     -.227709     -.13709
           foreigners |  -.0245444   .0365569    -0.67   0.503    -.0970066    .0479177
       pop_density_16 |   .0002205   .0001024     2.15   0.033     .0000176    .0004234
                _cons |   75.96164   2.074752    36.61   0.000     71.84912    80.07416
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,781
Absorbing 1 HDFE group                            F(  10,    108) =     125.67
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7121
                                                  Adj R-squared   =     0.7077
                                                  Within R-sq.    =     0.3448
Number of clusters (province_id) =        109     Root MSE        =     4.6891

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2071338   .0760786     2.72   0.008     .0563328    .3579349
             m5s_c_13 |   .2472873   .0513882     4.81   0.000     .1454271    .3491476
              pd_c_13 |   -.513199   .0335999   -15.27   0.000    -.5797998   -.4465982
           turnout_13 |   .0037261    .035718     0.10   0.917    -.0670731    .0745253
               income |  -.0004794   .0000942    -5.09   0.000    -.0006661   -.0002927
         unemployment |   .1788739   .0272014     6.58   0.000      .124956    .2327918
           university |  -.2594079   .0576962    -4.50   0.000    -.3737716   -.1450441
               no_edu |  -.1829041    .022787    -8.03   0.000    -.2280719   -.1377362
           foreigners |  -.0240059   .0364934    -0.66   0.512    -.0963422    .0483304
       pop_density_16 |   .0002168   .0001022     2.12   0.036     .0000143    .0004194
                _cons |   76.20528   2.063529    36.93   0.000     72.11501    80.29555
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,778
Absorbing 1 HDFE group                            F(  10,    108) =     125.50
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7128
                                                  Adj R-squared   =     0.7083
                                                  Within R-sq.    =     0.3451
Number of clusters (province_id) =        109     Root MSE        =     4.6893

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .1953051   .0750821     2.60   0.011     .0464793    .3441309
             m5s_c_13 |   .2473871   .0513986     4.81   0.000     .1455061     .349268
              pd_c_13 |  -.5134802   .0335497   -15.31   0.000    -.5799815   -.4469789
           turnout_13 |   .0032376   .0357502     0.09   0.928    -.0676255    .0741007
               income |  -.0004814   .0000942    -5.11   0.000    -.0006682   -.0002946
         unemployment |   .1783286    .027215     6.55   0.000     .1243838    .2322733
           university |  -.2532417   .0575222    -4.40   0.000    -.3672608   -.1392226
               no_edu |  -.1817711   .0227719    -7.98   0.000     -.226909   -.1366331
           foreigners |  -.0243134    .036554    -0.67   0.507    -.0967697    .0481429
       pop_density_16 |   .0002175   .0001023     2.12   0.036     .0000146    .0004204
                _cons |   76.21644   2.061669    36.97   0.000     72.12985    80.30302
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,716
Absorbing 1 HDFE group                            F(  10,    108) =     124.02
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7104
                                                  Adj R-squared   =     0.7059
                                                  Within R-sq.    =     0.3446
Number of clusters (province_id) =        109     Root MSE        =     4.6784

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2091414   .0759771     2.75   0.007     .0585417    .3597412
             m5s_c_13 |   .2467438   .0518558     4.76   0.000     .1439566     .349531
              pd_c_13 |  -.5123905   .0337823   -15.17   0.000    -.5793529   -.4454281
           turnout_13 |   .0047373   .0359357     0.13   0.895    -.0664935    .0759681
               income |  -.0004727   .0000946    -4.99   0.000    -.0006603   -.0002851
         unemployment |   .1840542   .0278478     6.61   0.000     .1288551    .2392534
           university |  -.2660047   .0575188    -4.62   0.000     -.380017   -.1519924
               no_edu |  -.1802269   .0228624    -7.88   0.000    -.2255442   -.1349097
           foreigners |  -.0246958   .0365236    -0.68   0.500    -.0970919    .0477003
       pop_density_16 |   .0002215   .0001016     2.18   0.031       .00002    .0004229
                _cons |   75.88086   2.065862    36.73   0.000     71.78597    79.97576
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,700
Absorbing 1 HDFE group                            F(  10,    108) =     124.71
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7115
                                                  Adj R-squared   =     0.7070
                                                  Within R-sq.    =     0.3438
Number of clusters (province_id) =        109     Root MSE        =     4.7103

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .1941946   .0762138     2.55   0.012     .0431256    .3452637
             m5s_c_13 |   .2476432   .0515825     4.80   0.000     .1453978    .3498886
              pd_c_13 |  -.5132886   .0337779   -15.20   0.000    -.5802423    -.446335
           turnout_13 |   .0025711   .0358532     0.07   0.943    -.0684962    .0736385
               income |  -.0004734   .0000947    -5.00   0.000    -.0006611   -.0002857
         unemployment |   .1783456   .0271331     6.57   0.000     .1245631    .2321281
           university |  -.2536373   .0580557    -4.37   0.000    -.3687138   -.1385608
               no_edu |  -.1833383   .0228089    -8.04   0.000    -.2285496    -.138127
           foreigners |  -.0217549   .0368199    -0.59   0.556    -.0947383    .0512286
       pop_density_16 |   .0002307   .0001011     2.28   0.024     .0000304     .000431
                _cons |      76.15   2.058004    37.00   0.000     72.07068    80.22932
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,722
Absorbing 1 HDFE group                            F(  10,    108) =     119.44
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7145
                                                  Adj R-squared   =     0.7100
                                                  Within R-sq.    =     0.3474
Number of clusters (province_id) =        109     Root MSE        =     4.6554

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2007668     .07676     2.62   0.010     .0486151    .3529185
             m5s_c_13 |    .250304   .0516612     4.85   0.000     .1479025    .3527056
              pd_c_13 |   -.513595   .0338457   -15.17   0.000    -.5806829    -.446507
           turnout_13 |   .0034669   .0363265     0.10   0.924    -.0685386    .0754725
               income |  -.0004856   .0000944    -5.14   0.000    -.0006727   -.0002984
         unemployment |   .1759509   .0275333     6.39   0.000     .1213751    .2305268
           university |  -.2567031   .0579562    -4.43   0.000    -.3715824   -.1418238
               no_edu |  -.1844982   .0230677    -8.00   0.000    -.2302224   -.1387741
           foreigners |  -.0216239   .0364863    -0.59   0.555     -.093946    .0506982
       pop_density_16 |   .0001818   .0001029     1.77   0.080     -.000022    .0003857
                _cons |   76.31329     2.0849    36.60   0.000     72.18065    80.44592
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,761
Absorbing 1 HDFE group                            F(  10,    108) =     125.85
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7121
                                                  Adj R-squared   =     0.7076
                                                  Within R-sq.    =     0.3446
Number of clusters (province_id) =        109     Root MSE        =     4.6984

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2112234   .0765307     2.76   0.007     .0595262    .3629206
             m5s_c_13 |   .2464629   .0515194     4.78   0.000     .1443425    .3485833
              pd_c_13 |  -.5130925   .0335708   -15.28   0.000    -.5796357   -.4465493
           turnout_13 |   .0034029   .0357972     0.10   0.924    -.0675535    .0743592
               income |  -.0004767   .0000948    -5.03   0.000    -.0006646   -.0002889
         unemployment |   .1776807   .0271168     6.55   0.000     .1239306    .2314308
           university |  -.2588653   .0578222    -4.48   0.000    -.3734789   -.1442516
               no_edu |  -.1823017   .0227822    -8.00   0.000    -.2274599   -.1371435
           foreigners |  -.0235803   .0368853    -0.64   0.524    -.0966933    .0495327
       pop_density_16 |   .0002178   .0001025     2.12   0.036     .0000146     .000421
                _cons |   76.23312   2.074913    36.74   0.000     72.12029    80.34596
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,622
Absorbing 1 HDFE group                            F(  10,    108) =     120.87
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7148
                                                  Adj R-squared   =     0.7103
                                                  Within R-sq.    =     0.3436
Number of clusters (province_id) =        109     Root MSE        =     4.7091

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |    .207071   .0779033     2.66   0.009     .0526532    .3614888
             m5s_c_13 |    .247809   .0520547     4.76   0.000     .1446276    .3509904
              pd_c_13 |   -.511972   .0339451   -15.08   0.000     -.579257   -.4446869
           turnout_13 |   .0019637   .0363269     0.05   0.957    -.0700425      .07397
               income |  -.0004782   .0000963    -4.97   0.000    -.0006691   -.0002873
         unemployment |   .1769194   .0274573     6.44   0.000     .1224943    .2313445
           university |  -.2568425   .0596818    -4.30   0.000    -.3751422   -.1385429
               no_edu |  -.1848235   .0231447    -7.99   0.000    -.2307002   -.1389468
           foreigners |  -.0233546    .037284    -0.63   0.532     -.097258    .0505489
       pop_density_16 |   .0002187   .0001023     2.14   0.035     .0000159    .0004216
                _cons |   76.31279   2.077104    36.74   0.000     72.19561    80.42997
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,745
Absorbing 1 HDFE group                            F(  10,    108) =     124.51
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7101
                                                  Adj R-squared   =     0.7056
                                                  Within R-sq.    =     0.3441
Number of clusters (province_id) =        109     Root MSE        =     4.6984

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2027898   .0771167     2.63   0.010     .0499311    .3556485
             m5s_c_13 |   .2449356   .0516772     4.74   0.000     .1425025    .3473687
              pd_c_13 |  -.5159309   .0339232   -15.21   0.000    -.5831725   -.4486892
           turnout_13 |   .0025934   .0358393     0.07   0.942    -.0684462    .0736331
               income |  -.0004752   .0000941    -5.05   0.000    -.0006617   -.0002887
         unemployment |   .1779045   .0271795     6.55   0.000     .1240301    .2317789
           university |  -.2592426    .057863    -4.48   0.000     -.373937   -.1445482
               no_edu |  -.1830819   .0228663    -8.01   0.000     -.228407   -.1377569
           foreigners |  -.0258543   .0368229    -0.70   0.484    -.0988438    .0471351
       pop_density_16 |   .0002216   .0001018     2.18   0.032     .0000198    .0004234
                _cons |   76.43588   2.061056    37.09   0.000     72.35051    80.52125
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,746
Absorbing 1 HDFE group                            F(  10,    108) =     125.86
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7119
                                                  Adj R-squared   =     0.7074
                                                  Within R-sq.    =     0.3447
Number of clusters (province_id) =        109     Root MSE        =     4.6953

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2073579   .0761547     2.72   0.008     .0564061    .3583097
             m5s_c_13 |   .2487202   .0516893     4.81   0.000     .1462631    .3511773
              pd_c_13 |  -.5132227   .0336943   -15.23   0.000    -.5800107   -.4464347
           turnout_13 |   .0027814   .0358031     0.08   0.938    -.0681865    .0737493
               income |  -.0004779   .0000944    -5.06   0.000    -.0006651   -.0002907
         unemployment |   .1787159   .0272078     6.57   0.000     .1247854    .2326464
           university |   -.261103   .0580013    -4.50   0.000    -.3760717   -.1461343
               no_edu |  -.1829465   .0228643    -8.00   0.000    -.2282676   -.1376254
           foreigners |  -.0254535   .0366473    -0.69   0.489    -.0980948    .0471879
       pop_density_16 |   .0002196   .0001018     2.16   0.033     .0000178    .0004213
                _cons |   76.32077   2.064139    36.97   0.000     72.22928    80.41225
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,758
Absorbing 1 HDFE group                            F(  10,    108) =     129.18
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7137
                                                  Adj R-squared   =     0.7093
                                                  Within R-sq.    =     0.3466
Number of clusters (province_id) =        109     Root MSE        =     4.6869

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2029253    .076262     2.66   0.009     .0517609    .3540898
             m5s_c_13 |   .2503165   .0513381     4.88   0.000     .1485555    .3520774
              pd_c_13 |  -.5125512   .0336265   -15.24   0.000    -.5792048   -.4458975
           turnout_13 |  -.0000765   .0356916    -0.00   0.998    -.0708235    .0706705
               income |  -.0004769   .0000942    -5.06   0.000    -.0006636   -.0002902
         unemployment |   .1792517   .0272206     6.59   0.000     .1252956    .2332077
           university |  -.2610739   .0577747    -4.52   0.000    -.3755934   -.1465544
               no_edu |  -.1850642   .0228322    -8.11   0.000    -.2303216   -.1398067
           foreigners |  -.0248664   .0365304    -0.68   0.498    -.0972759    .0475431
       pop_density_16 |   .0002161   .0001023     2.11   0.037     .0000134    .0004189
                _cons |   76.48884   2.050738    37.30   0.000     72.42392    80.55376
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,757
Absorbing 1 HDFE group                            F(  10,    108) =     126.39
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7130
                                                  Adj R-squared   =     0.7086
                                                  Within R-sq.    =     0.3452
Number of clusters (province_id) =        109     Root MSE        =     4.6971

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2051403   .0761319     2.69   0.008     .0542336    .3560469
             m5s_c_13 |   .2474452   .0513432     4.82   0.000     .1456741    .3492162
              pd_c_13 |  -.5122897   .0335762   -15.26   0.000    -.5788436   -.4457358
           turnout_13 |   .0018595   .0358809     0.05   0.959    -.0692627    .0729817
               income |  -.0004757   .0000945    -5.03   0.000    -.0006631   -.0002884
         unemployment |   .1797028   .0272454     6.60   0.000     .1256978    .2337078
           university |  -.2589891   .0577707    -4.48   0.000    -.3735005   -.1444776
               no_edu |  -.1832192   .0229972    -7.97   0.000    -.2288036   -.1376349
           foreigners |  -.0222802    .036781    -0.61   0.546    -.0951865    .0506261
       pop_density_16 |   .0002144   .0001024     2.09   0.039     .0000115    .0004173
                _cons |   76.27866   2.065725    36.93   0.000     72.18403    80.37329
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,769
Absorbing 1 HDFE group                            F(  10,    108) =     125.92
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7109
                                                  Adj R-squared   =     0.7065
                                                  Within R-sq.    =     0.3449
Number of clusters (province_id) =        109     Root MSE        =     4.6924

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .1999392   .0755168     2.65   0.009     .0502518    .3496266
             m5s_c_13 |   .2474223   .0512895     4.82   0.000     .1457577    .3490869
              pd_c_13 |  -.5131487   .0335618   -15.29   0.000    -.5796739   -.4466234
           turnout_13 |   .0039984   .0357312     0.11   0.911     -.066827    .0748238
               income |  -.0004713   .0000949    -4.96   0.000    -.0006595   -.0002831
         unemployment |   .1781484   .0271415     6.56   0.000     .1243493    .2319476
           university |  -.2672908    .057539    -4.65   0.000    -.3813431   -.1532385
               no_edu |  -.1825191   .0227683    -8.02   0.000    -.2276498   -.1373884
           foreigners |  -.0237612   .0366932    -0.65   0.519    -.0964934     .048971
       pop_density_16 |   .0002242   .0001016     2.21   0.029     .0000228    .0004255
                _cons |   76.18093   2.062587    36.93   0.000     72.09253    80.26934
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,782
Absorbing 1 HDFE group                            F(  10,    108) =     126.14
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7113
                                                  Adj R-squared   =     0.7069
                                                  Within R-sq.    =     0.3450
Number of clusters (province_id) =        109     Root MSE        =     4.6934

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2072534   .0762134     2.72   0.008     .0561853    .3583215
             m5s_c_13 |   .2470063   .0513039     4.81   0.000      .145313    .3486996
              pd_c_13 |  -.5135408   .0335252   -15.32   0.000    -.5799936    -.447088
           turnout_13 |    .003789   .0357744     0.11   0.916     -.067122    .0747001
               income |  -.0004787   .0000941    -5.09   0.000    -.0006653   -.0002921
         unemployment |   .1779171   .0271139     6.56   0.000     .1241727    .2316614
           university |   -.258625   .0576188    -4.49   0.000    -.3728356   -.1444145
               no_edu |  -.1826261   .0227294    -8.03   0.000    -.2276797   -.1375725
           foreigners |  -.0239466   .0365378    -0.66   0.514    -.0963708    .0484776
       pop_density_16 |   .0002188   .0001023     2.14   0.035      .000016    .0004216
                _cons |   76.24501   2.061729    36.98   0.000     72.15831    80.33172
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,704
Absorbing 1 HDFE group                            F(  10,    108) =     178.92
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7188
                                                  Adj R-squared   =     0.7144
                                                  Within R-sq.    =     0.3523
Number of clusters (province_id) =        109     Root MSE        =     4.6483

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2008082   .0760076     2.64   0.009      .050148    .3514684
             m5s_c_13 |   .2541184   .0515077     4.93   0.000     .1520213    .3562156
              pd_c_13 |  -.5232428   .0325586   -16.07   0.000    -.5877797   -.4587059
           turnout_13 |   .0019339   .0364277     0.05   0.958    -.0702721    .0741399
               income |  -.0004856   .0000943    -5.15   0.000    -.0006725   -.0002988
         unemployment |   .1851071   .0273084     6.78   0.000     .1309771    .2392371
           university |  -.2462969   .0570559    -4.32   0.000    -.3593916   -.1332021
               no_edu |  -.1788298   .0228297    -7.83   0.000    -.2240822   -.1335774
           foreigners |  -.0244389   .0366223    -0.67   0.506    -.0970307    .0481528
       pop_density_16 |   .0002126   .0001011     2.10   0.038     .0000122     .000413
                _cons |   76.17941   2.115551    36.01   0.000     71.98602     80.3728
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,797
Absorbing 1 HDFE group                            F(  10,    108) =     126.20
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7116
                                                  Adj R-squared   =     0.7072
                                                  Within R-sq.    =     0.3450
Number of clusters (province_id) =        109     Root MSE        =     4.6905

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2051902   .0760748     2.70   0.008     .0543968    .3559836
             m5s_c_13 |   .2466712   .0513034     4.81   0.000      .144979    .3483633
              pd_c_13 |  -.5132762   .0334959   -15.32   0.000    -.5796709   -.4468814
           turnout_13 |   .0032494   .0357202     0.09   0.928    -.0675543     .074053
               income |  -.0004787   .0000941    -5.09   0.000    -.0006652   -.0002922
         unemployment |   .1779233   .0271075     6.56   0.000     .1241915    .2316551
           university |   -.257893   .0575668    -4.48   0.000    -.3720005   -.1437856
               no_edu |  -.1827084   .0227214    -8.04   0.000    -.2277462   -.1376705
           foreigners |  -.0239573    .036537    -0.66   0.513    -.0963799    .0484653
       pop_density_16 |   .0002158   .0001026     2.10   0.038     .0000125    .0004192
                _cons |   76.27523   2.059288    37.04   0.000     72.19336    80.35709
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,755
Absorbing 1 HDFE group                            F(  10,    108) =     125.30
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7130
                                                  Adj R-squared   =     0.7086
                                                  Within R-sq.    =     0.3444
Number of clusters (province_id) =        109     Root MSE        =     4.6951

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2089923   .0768593     2.72   0.008     .0566438    .3613407
             m5s_c_13 |   .2461866   .0514449     4.79   0.000     .1442139    .3481592
              pd_c_13 |   -.512217   .0335723   -15.26   0.000    -.5787632   -.4456708
           turnout_13 |   .0062533   .0358312     0.17   0.862    -.0647703    .0772769
               income |  -.0004843   .0000941    -5.15   0.000    -.0006708   -.0002977
         unemployment |   .1771148   .0271126     6.53   0.000     .1233729    .2308567
           university |  -.2549637   .0576971    -4.42   0.000    -.3693294    -.140598
               no_edu |  -.1828471   .0228076    -8.02   0.000    -.2280556   -.1376385
           foreigners |  -.0223344   .0366769    -0.61   0.544    -.0950345    .0503657
       pop_density_16 |   .0002155    .000103     2.09   0.039     .0000113    .0004197
                _cons |   76.06995   2.061015    36.91   0.000     71.98466    80.15523
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,792
Absorbing 1 HDFE group                            F(  10,    108) =     125.74
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7126
                                                  Adj R-squared   =     0.7082
                                                  Within R-sq.    =     0.3450
Number of clusters (province_id) =        109     Root MSE        =     4.6888

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2064703   .0760757     2.71   0.008     .0556752    .3572655
             m5s_c_13 |   .2476255   .0513352     4.82   0.000     .1458701    .3493808
              pd_c_13 |  -.5134826   .0334949   -15.33   0.000    -.5798753   -.4470899
           turnout_13 |    .004228   .0357256     0.12   0.906    -.0665864    .0750424
               income |  -.0004772   .0000941    -5.07   0.000    -.0006637   -.0002907
         unemployment |   .1775829   .0271268     6.55   0.000     .1238128    .2313529
           university |  -.2572109    .057545    -4.47   0.000    -.3712752   -.1431467
               no_edu |  -.1814856   .0227213    -7.99   0.000    -.2265232   -.1364481
           foreigners |  -.0252746   .0366817    -0.69   0.492    -.0979842    .0474349
       pop_density_16 |   .0002148   .0001026     2.09   0.039     .0000114    .0004183
                _cons |   76.12777   2.056586    37.02   0.000     72.05126    80.20428
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,786
Absorbing 1 HDFE group                            F(  10,    108) =     126.08
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7110
                                                  Adj R-squared   =     0.7065
                                                  Within R-sq.    =     0.3451
Number of clusters (province_id) =        109     Root MSE        =     4.6925

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2064647    .076417     2.70   0.008      .054993    .3579364
             m5s_c_13 |   .2465572   .0513381     4.80   0.000     .1447962    .3483181
              pd_c_13 |   -.513911   .0335554   -15.32   0.000    -.5804237   -.4473983
           turnout_13 |   .0033451   .0357077     0.09   0.926    -.0674337    .0741239
               income |  -.0004795   .0000941    -5.10   0.000     -.000666    -.000293
         unemployment |   .1774654   .0270963     6.55   0.000     .1237558    .2311749
           university |  -.2577267   .0576158    -4.47   0.000    -.3719311   -.1435223
               no_edu |  -.1829339   .0227279    -8.05   0.000    -.2279845   -.1378834
           foreigners |  -.0242572   .0365601    -0.66   0.508    -.0967256    .0482113
       pop_density_16 |   .0002174   .0001023     2.13   0.036     .0000147    .0004201
                _cons |   76.30288   2.056672    37.10   0.000      72.2262    80.37956
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,707
Absorbing 1 HDFE group                            F(  10,    108) =     127.44
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7157
                                                  Adj R-squared   =     0.7113
                                                  Within R-sq.    =     0.3439
Number of clusters (province_id) =        109     Root MSE        =     4.6562

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2066579   .0760773     2.72   0.008     .0558596    .3574563
             m5s_c_13 |   .2417585   .0518473     4.66   0.000     .1389882    .3445288
              pd_c_13 |  -.5061544   .0332361   -15.23   0.000    -.5720341   -.4402746
           turnout_13 |    .001816   .0366353     0.05   0.961    -.0708015    .0744335
               income |   -.000458   .0000929    -4.93   0.000    -.0006422   -.0002738
         unemployment |   .1906389   .0262602     7.26   0.000     .1385867    .2426912
           university |  -.2746434   .0557691    -4.92   0.000    -.3851875   -.1640993
               no_edu |  -.1826131   .0232717    -7.85   0.000    -.2287415   -.1364846
           foreigners |   -.028127   .0367794    -0.76   0.446    -.1010301    .0447761
       pop_density_16 |   .0002084   .0001018     2.05   0.043     6.51e-06    .0004102
                _cons |   76.07797   2.122908    35.84   0.000        71.87    80.28595
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,763
Absorbing 1 HDFE group                            F(  10,    108) =     125.23
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7100
                                                  Adj R-squared   =     0.7055
                                                  Within R-sq.    =     0.3445
Number of clusters (province_id) =        109     Root MSE        =     4.6986

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2058532   .0762259     2.70   0.008     .0547603    .3569461
             m5s_c_13 |   .2471793    .051385     4.81   0.000     .1453253    .3490334
              pd_c_13 |  -.5140475   .0336003   -15.30   0.000    -.5806491   -.4474459
           turnout_13 |   .0033721   .0357087     0.09   0.925    -.0674088    .0741529
               income |  -.0004776   .0000943    -5.06   0.000    -.0006645   -.0002907
         unemployment |   .1777177   .0271004     6.56   0.000         .124    .2314355
           university |  -.2578324   .0576781    -4.47   0.000    -.3721603   -.1435044
               no_edu |  -.1822267   .0227571    -8.01   0.000    -.2273352   -.1371182
           foreigners |  -.0235554   .0366666    -0.64   0.522     -.096235    .0491243
       pop_density_16 |   .0002155   .0001025     2.10   0.038     .0000124    .0004187
                _cons |   76.24168   2.057608    37.05   0.000     72.16314    80.32022
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,731
Absorbing 1 HDFE group                            F(  10,    108) =     132.89
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7157
                                                  Adj R-squared   =     0.7113
                                                  Within R-sq.    =     0.3498
Number of clusters (province_id) =        109     Root MSE        =     4.6774

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2081102   .0774624     2.69   0.008     .0545663    .3616541
             m5s_c_13 |   .2484955   .0517849     4.80   0.000     .1458488    .3511423
              pd_c_13 |  -.5153793   .0338049   -15.25   0.000    -.5823866    -.448372
           turnout_13 |   .0072751   .0359289     0.20   0.840    -.0639422    .0784925
               income |  -.0004802   .0000941    -5.10   0.000    -.0006667   -.0002936
         unemployment |   .1764295   .0275715     6.40   0.000     .1217781    .2310809
           university |  -.2683479   .0570156    -4.71   0.000    -.3813626   -.1553331
               no_edu |   -.187055   .0226481    -8.26   0.000    -.2319475   -.1421626
           foreigners |  -.0241483   .0368517    -0.66   0.514    -.0971947     .048898
       pop_density_16 |   .0002143   .0001024     2.09   0.039     .0000113    .0004172
                _cons |   76.21436   2.079669    36.65   0.000      72.0921    80.33663
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,781
Absorbing 1 HDFE group                            F(  10,    108) =     125.76
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7124
                                                  Adj R-squared   =     0.7079
                                                  Within R-sq.    =     0.3446
Number of clusters (province_id) =        109     Root MSE        =     4.6930

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |    .208619   .0764252     2.73   0.007      .057131    .3601071
             m5s_c_13 |   .2473238    .051351     4.82   0.000     .1455373    .3491104
              pd_c_13 |  -.5131084   .0335157   -15.31   0.000    -.5795425   -.4466744
           turnout_13 |   .0035647   .0357188     0.10   0.921    -.0672361    .0743655
               income |  -.0004771   .0000943    -5.06   0.000     -.000664   -.0002903
         unemployment |   .1778749   .0271126     6.56   0.000     .1241329    .2316168
           university |  -.2576764   .0576117    -4.47   0.000    -.3718727   -.1434801
               no_edu |  -.1821279   .0227394    -8.01   0.000    -.2272013   -.1370545
           foreigners |   -.023871   .0365571    -0.65   0.515    -.0963335    .0485915
       pop_density_16 |   .0002179   .0001029     2.12   0.036      .000014    .0004219
                _cons |       76.2   2.060871    36.97   0.000     72.11499      80.285
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,683
Absorbing 1 HDFE group                            F(  10,    108) =     120.12
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7135
                                                  Adj R-squared   =     0.7090
                                                  Within R-sq.    =     0.3440
Number of clusters (province_id) =        109     Root MSE        =     4.6940

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2206009   .0790693     2.79   0.006     .0638717      .37733
             m5s_c_13 |   .2456992   .0526287     4.67   0.000       .14138    .3500184
              pd_c_13 |  -.5189445   .0334814   -15.50   0.000    -.5853104   -.4525787
           turnout_13 |   .0039007   .0363633     0.11   0.915    -.0681777    .0759792
               income |   -.000473   .0000948    -4.99   0.000    -.0006609   -.0002851
         unemployment |   .1759528   .0272403     6.46   0.000     .1219579    .2299477
           university |  -.2487729   .0575675    -4.32   0.000    -.3628818   -.1346641
               no_edu |  -.1806884   .0228349    -7.91   0.000     -.225951   -.1354257
           foreigners |  -.0248339   .0375044    -0.66   0.509    -.0991742    .0495064
       pop_density_16 |   .0002267   .0001026     2.21   0.029     .0000233    .0004301
                _cons |   76.10666   2.070327    36.76   0.000     72.00291     80.2104
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,754
Absorbing 1 HDFE group                            F(  10,    108) =     124.95
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7129
                                                  Adj R-squared   =     0.7085
                                                  Within R-sq.    =     0.3441
Number of clusters (province_id) =        109     Root MSE        =     4.6974

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2051254   .0760749     2.70   0.008     .0543316    .3559191
             m5s_c_13 |   .2457965   .0513998     4.78   0.000     .1439131    .3476798
              pd_c_13 |  -.5123579   .0336496   -15.23   0.000    -.5790573   -.4456586
           turnout_13 |   .0025611   .0357626     0.07   0.943    -.0683266    .0734488
               income |  -.0004764   .0000943    -5.05   0.000    -.0006634   -.0002894
         unemployment |   .1782338   .0271258     6.57   0.000     .1244657    .2320018
           university |  -.2590898   .0577327    -4.49   0.000    -.3735261   -.1446535
               no_edu |  -.1837195   .0227896    -8.06   0.000    -.2288925   -.1385465
           foreigners |  -.0217982    .036624    -0.60   0.553    -.0943933    .0507969
       pop_density_16 |   .0002151   .0001026     2.10   0.038     .0000117    .0004185
                _cons |   76.29781   2.057054    37.09   0.000     72.22037    80.37525
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,646
Absorbing 1 HDFE group                            F(  10,    108) =     114.27
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7166
                                                  Adj R-squared   =     0.7122
                                                  Within R-sq.    =     0.3397
Number of clusters (province_id) =        109     Root MSE        =     4.6637

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2144184   .0770259     2.78   0.006     .0617398    .3670971
             m5s_c_13 |   .2513078   .0520127     4.83   0.000     .1482097     .354406
              pd_c_13 |  -.5056814   .0338077   -14.96   0.000    -.5726941   -.4386688
           turnout_13 |   -.001802   .0362091    -0.05   0.960    -.0735747    .0699707
               income |  -.0004864   .0000949    -5.13   0.000    -.0006745   -.0002983
         unemployment |   .1814164   .0283634     6.40   0.000     .1251953    .2376376
           university |  -.2577986   .0591112    -4.36   0.000    -.3749673   -.1406299
               no_edu |  -.1834706   .0235057    -7.81   0.000    -.2300631   -.1368782
           foreigners |  -.0276018    .036616    -0.75   0.453    -.1001811    .0449774
       pop_density_16 |   .0001984   .0001074     1.85   0.068    -.0000146    .0004113
                _cons |   76.51903   2.086345    36.68   0.000     72.38353    80.65453
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,738
Absorbing 1 HDFE group                            F(  10,    108) =     122.80
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7132
                                                  Adj R-squared   =     0.7087
                                                  Within R-sq.    =     0.3435
Number of clusters (province_id) =        109     Root MSE        =     4.6840

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2018189   .0760394     2.65   0.009     .0510957    .3525422
             m5s_c_13 |   .2461059    .051853     4.75   0.000     .1433242    .3488876
              pd_c_13 |  -.5149746   .0338119   -15.23   0.000    -.5819955   -.4479536
           turnout_13 |   .0027667   .0359701     0.08   0.939    -.0685322    .0740656
               income |  -.0004833   .0000944    -5.12   0.000    -.0006704   -.0002961
         unemployment |   .1776463   .0275507     6.45   0.000     .1230361    .2322566
           university |   -.252666   .0577719    -4.37   0.000    -.3671798   -.1381521
               no_edu |  -.1790132   .0226473    -7.90   0.000    -.2239042   -.1341223
           foreigners |  -.0214599   .0364895    -0.59   0.558    -.0937884    .0508686
       pop_density_16 |   .0002229   .0001024     2.18   0.032       .00002    .0004259
                _cons |   76.18422   2.075059    36.71   0.000     72.07109    80.29734
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,736
Absorbing 1 HDFE group                            F(  10,    108) =     126.82
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7137
                                                  Adj R-squared   =     0.7093
                                                  Within R-sq.    =     0.3453
Number of clusters (province_id) =        109     Root MSE        =     4.6936

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2042216   .0768313     2.66   0.009     .0519287    .3565146
             m5s_c_13 |    .248036   .0514877     4.82   0.000     .1459784    .3500936
              pd_c_13 |  -.5148473   .0335947   -15.33   0.000    -.5814378   -.4482567
           turnout_13 |   .0026424   .0358185     0.07   0.941    -.0683561    .0736409
               income |  -.0004967   .0000936    -5.31   0.000    -.0006821   -.0003112
         unemployment |   .1765412   .0271528     6.50   0.000     .1227197    .2303627
           university |  -.2488111   .0574954    -4.33   0.000    -.3627769   -.1348452
               no_edu |  -.1827113   .0228716    -7.99   0.000    -.2280469   -.1373758
           foreigners |  -.0236575   .0367519    -0.64   0.521    -.0965061    .0491911
       pop_density_16 |   .0002182   .0001024     2.13   0.035     .0000152    .0004212
                _cons |   76.47649   2.053607    37.24   0.000     72.40588    80.54709
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,768
Absorbing 1 HDFE group                            F(  10,    108) =     126.05
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7072
                                                  Adj R-squared   =     0.7027
                                                  Within R-sq.    =     0.3451
Number of clusters (province_id) =        109     Root MSE        =     4.6952

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2015246   .0761019     2.65   0.009     .0506774    .3523717
             m5s_c_13 |   .2466816   .0513227     4.81   0.000     .1449511     .348412
              pd_c_13 |  -.5136382   .0335665   -15.30   0.000    -.5801729   -.4471035
           turnout_13 |   .0028434   .0357066     0.08   0.937    -.0679333    .0736201
               income |  -.0004752   .0000944    -5.03   0.000    -.0006623   -.0002881
         unemployment |   .1776884   .0270948     6.56   0.000     .1239818    .2313949
           university |    -.26148   .0577655    -4.53   0.000    -.3759812   -.1469789
               no_edu |  -.1827758   .0227681    -8.03   0.000    -.2279062   -.1376454
           foreigners |  -.0224407   .0367429    -0.61   0.543    -.0952715    .0503901
       pop_density_16 |   .0002194   .0001022     2.15   0.034     .0000169     .000422
                _cons |   76.31011   2.057544    37.09   0.000      72.2317    80.38852
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,783
Absorbing 1 HDFE group                            F(  10,    108) =     125.71
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7118
                                                  Adj R-squared   =     0.7073
                                                  Within R-sq.    =     0.3442
Number of clusters (province_id) =        109     Root MSE        =     4.6898

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |    .197689   .0763165     2.59   0.011     .0464164    .3489616
             m5s_c_13 |   .2483227   .0515104     4.82   0.000     .1462201    .3504253
              pd_c_13 |  -.5123402   .0335159   -15.29   0.000    -.5787746   -.4459058
           turnout_13 |   .0032498   .0357164     0.09   0.928    -.0675463     .074046
               income |  -.0004761   .0000945    -5.04   0.000    -.0006635   -.0002887
         unemployment |   .1762432   .0271031     6.50   0.000     .1225201    .2299663
           university |   -.256859   .0576716    -4.45   0.000     -.371174   -.1425439
               no_edu |  -.1814366   .0227439    -7.98   0.000     -.226519   -.1363541
           foreigners |  -.0230514   .0365171    -0.63   0.529    -.0954346    .0493318
       pop_density_16 |   .0002145   .0001031     2.08   0.040     .0000102    .0004188
                _cons |   76.14218   2.062573    36.92   0.000      72.0538    80.23056
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,731
Absorbing 1 HDFE group                            F(  10,    108) =     125.37
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7149
                                                  Adj R-squared   =     0.7104
                                                  Within R-sq.    =     0.3463
Number of clusters (province_id) =        109     Root MSE        =     4.6779

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2033572   .0762635     2.67   0.009     .0521897    .3545247
             m5s_c_13 |   .2489651   .0517417     4.81   0.000     .1464041    .3515262
              pd_c_13 |  -.5112199   .0338399   -15.11   0.000    -.5782964   -.4441435
           turnout_13 |    .004039   .0362933     0.11   0.912    -.0679006    .0759786
               income |  -.0004933   .0000944    -5.23   0.000    -.0006804   -.0003062
         unemployment |   .1758081   .0271194     6.48   0.000     .1220528    .2295633
           university |  -.2488201    .057276    -4.34   0.000    -.3623511   -.1352892
               no_edu |   -.182181   .0229005    -7.96   0.000    -.2275737   -.1367883
           foreigners |  -.0277457   .0366461    -0.76   0.451    -.1003847    .0448934
       pop_density_16 |   .0002232   .0001019     2.19   0.031     .0000212    .0004251
                _cons |   76.23888   2.074247    36.75   0.000     72.12736     80.3504
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,775
Absorbing 1 HDFE group                            F(  10,    108) =     126.03
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7118
                                                  Adj R-squared   =     0.7074
                                                  Within R-sq.    =     0.3453
Number of clusters (province_id) =        109     Root MSE        =     4.6953

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2154525   .0764944     2.82   0.006     .0638273    .3670778
             m5s_c_13 |   .2472481    .051497     4.80   0.000      .145172    .3493241
              pd_c_13 |  -.5137731   .0335491   -15.31   0.000    -.5802732   -.4472729
           turnout_13 |   .0034806   .0358337     0.10   0.923     -.067548    .0745093
               income |  -.0004793   .0000942    -5.09   0.000    -.0006661   -.0002926
         unemployment |   .1771697   .0271553     6.52   0.000     .1233431    .2309962
           university |  -.2571941   .0576472    -4.46   0.000    -.3714609   -.1429274
               no_edu |  -.1824415   .0227483    -8.02   0.000    -.2275326   -.1373503
           foreigners |   -.023573   .0365042    -0.65   0.520    -.0959307    .0487847
       pop_density_16 |   .0002129   .0001028     2.07   0.041     9.15e-06    .0004166
                _cons |   76.23304   2.060235    37.00   0.000      72.1493    80.31679
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,757
Absorbing 1 HDFE group                            F(  10,    108) =     126.16
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7131
                                                  Adj R-squared   =     0.7087
                                                  Within R-sq.    =     0.3454
Number of clusters (province_id) =        109     Root MSE        =     4.6950

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2074291    .076425     2.71   0.008     .0559414    .3589168
             m5s_c_13 |   .2468473   .0517469     4.77   0.000     .1442761    .3494185
              pd_c_13 |   -.513749   .0336571   -15.26   0.000    -.5804632   -.4470348
           turnout_13 |   .0032239   .0358428     0.09   0.928    -.0678226    .0742705
               income |  -.0004803   .0000941    -5.10   0.000    -.0006669   -.0002937
         unemployment |    .177925    .027168     6.55   0.000     .1240733    .2317767
           university |  -.2585267   .0578339    -4.47   0.000    -.3731635     -.14389
               no_edu |   -.183368   .0228085    -8.04   0.000    -.2285784   -.1381577
           foreigners |  -.0231731   .0367522    -0.63   0.530    -.0960224    .0496761
       pop_density_16 |   .0002176   .0001023     2.13   0.036     .0000149    .0004204
                _cons |     76.311   2.060403    37.04   0.000     72.22692    80.39507
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,771
Absorbing 1 HDFE group                            F(  10,    108) =     124.93
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7121
                                                  Adj R-squared   =     0.7077
                                                  Within R-sq.    =     0.3437
Number of clusters (province_id) =        109     Root MSE        =     4.6924

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2077006   .0763673     2.72   0.008     .0563275    .3590738
             m5s_c_13 |   .2471426   .0513689     4.81   0.000     .1453206    .3489647
              pd_c_13 |  -.5120478   .0336124   -15.23   0.000    -.5786735   -.4454222
           turnout_13 |   .0032112   .0357272     0.09   0.929    -.0676063    .0740287
               income |  -.0004791   .0000942    -5.09   0.000    -.0006659   -.0002924
         unemployment |   .1775493   .0271074     6.55   0.000     .1238177    .2312809
           university |  -.2576296   .0576968    -4.47   0.000    -.3719948   -.1432645
               no_edu |  -.1823406   .0228199    -7.99   0.000    -.2275737   -.1371076
           foreigners |  -.0242781   .0366655    -0.66   0.509    -.0969555    .0483992
       pop_density_16 |   .0002162   .0001025     2.11   0.037      .000013    .0004194
                _cons |   76.24431   2.061127    36.99   0.000      72.1588    80.32982
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,505
Absorbing 1 HDFE group                            F(  10,    108) =     134.68
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7150
                                                  Adj R-squared   =     0.7105
                                                  Within R-sq.    =     0.3376
Number of clusters (province_id) =        109     Root MSE        =     4.7209

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .1998824   .0778705     2.57   0.012     .0455295    .3542353
             m5s_c_13 |   .2331272   .0540582     4.31   0.000     .1259746    .3402799
              pd_c_13 |  -.5145045   .0345542   -14.89   0.000    -.5829969    -.446012
           turnout_13 |   .0154803   .0350746     0.44   0.660    -.0540437    .0850042
               income |  -.0004961   .0000954    -5.20   0.000    -.0006852    -.000307
         unemployment |   .1728123   .0268676     6.43   0.000     .1195561    .2260686
           university |  -.2436753   .0585306    -4.16   0.000    -.3596932   -.1276575
               no_edu |  -.1838465   .0232287    -7.91   0.000    -.2298897   -.1378032
           foreigners |  -.0234415   .0375221    -0.62   0.533    -.0978168    .0509338
       pop_density_16 |    .000224   .0001083     2.07   0.041     9.33e-06    .0004386
                _cons |   75.90743   2.152275    35.27   0.000     71.64125    80.17362
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,780
Absorbing 1 HDFE group                            F(  10,    108) =     126.39
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7122
                                                  Adj R-squared   =     0.7078
                                                  Within R-sq.    =     0.3454
Number of clusters (province_id) =        109     Root MSE        =     4.6906

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2032447   .0771082     2.64   0.010     .0504028    .3560866
             m5s_c_13 |   .2493288   .0513415     4.86   0.000      .147561    .3510967
              pd_c_13 |  -.5126933   .0335045   -15.30   0.000     -.579105   -.4462815
           turnout_13 |      .0044   .0356875     0.12   0.902    -.0663388    .0751389
               income |  -.0004833   .0000941    -5.14   0.000    -.0006698   -.0002969
         unemployment |   .1802003   .0272657     6.61   0.000     .1261548    .2342457
           university |  -.2547636    .057589    -4.42   0.000     -.368915   -.1406123
               no_edu |  -.1809429   .0227334    -7.96   0.000    -.2260044   -.1358813
           foreigners |  -.0237726   .0364506    -0.65   0.516    -.0960241    .0484789
       pop_density_16 |   .0002148   .0001024     2.10   0.038     .0000118    .0004178
                _cons |   76.06937   2.060568    36.92   0.000     71.98497    80.15378
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,660
Absorbing 1 HDFE group                            F(  10,    108) =     123.95
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7164
                                                  Adj R-squared   =     0.7119
                                                  Within R-sq.    =     0.3492
Number of clusters (province_id) =        109     Root MSE        =     4.6565

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2010632   .0760674     2.64   0.009     .0502845     .351842
             m5s_c_13 |   .2350881     .05145     4.57   0.000     .1331053     .337071
              pd_c_13 |  -.5173957    .034244   -15.11   0.000    -.5852732   -.4495181
           turnout_13 |   .0111971   .0357842     0.31   0.755    -.0597334    .0821276
               income |  -.0004892   .0000943    -5.19   0.000    -.0006762   -.0003022
         unemployment |   .1775598    .027231     6.52   0.000     .1235832    .2315363
           university |  -.2522668   .0585113    -4.31   0.000    -.3682463   -.1362873
               no_edu |  -.1824668   .0229165    -7.96   0.000    -.2278913   -.1370424
           foreigners |  -.0158805   .0364553    -0.44   0.664    -.0881413    .0563802
       pop_density_16 |   .0002123   .0001049     2.02   0.045     4.39e-06    .0004201
                _cons |   76.09279   2.062314    36.90   0.000     72.00493    80.18065
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,709
Absorbing 1 HDFE group                            F(  10,    108) =     125.40
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7119
                                                  Adj R-squared   =     0.7074
                                                  Within R-sq.    =     0.3440
Number of clusters (province_id) =        109     Root MSE        =     4.7099

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2184928   .0762594     2.87   0.005     .0673333    .3696522
             m5s_c_13 |   .2471146   .0516356     4.79   0.000     .1447638    .3494653
              pd_c_13 |  -.5112882   .0337524   -15.15   0.000    -.5781913   -.4443851
           turnout_13 |   .0016936   .0359229     0.05   0.962    -.0695118     .072899
               income |  -.0004799   .0000948    -5.06   0.000    -.0006677   -.0002921
         unemployment |    .179011   .0271472     6.59   0.000     .1252005    .2328214
           university |  -.2538924   .0579191    -4.38   0.000    -.3686981   -.1390867
               no_edu |  -.1832107   .0227778    -8.04   0.000    -.2283604   -.1380611
           foreigners |    -.02313   .0367649    -0.63   0.531    -.0960045    .0497444
       pop_density_16 |   .0002143   .0001025     2.09   0.039      .000011    .0004175
                _cons |   76.28422   2.056579    37.09   0.000     72.20772    80.36072
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,799
Absorbing 1 HDFE group                            F(  10,    108) =     126.02
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7126
                                                  Adj R-squared   =     0.7082
                                                  Within R-sq.    =     0.3449
Number of clusters (province_id) =        109     Root MSE        =     4.6896

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2055884   .0763212     2.69   0.008     .0543065    .3568702
             m5s_c_13 |    .246449   .0513036     4.80   0.000     .1447564    .3481416
              pd_c_13 |  -.5133955   .0335016   -15.32   0.000    -.5798016   -.4469895
           turnout_13 |   .0034788   .0356943     0.10   0.923    -.0672736    .0742312
               income |   -.000479   .0000941    -5.09   0.000    -.0006655   -.0002925
         unemployment |   .1779714   .0271012     6.57   0.000     .1242521    .2316907
           university |  -.2570904   .0576255    -4.46   0.000    -.3713142   -.1428666
               no_edu |  -.1826777   .0227211    -8.04   0.000    -.2277148   -.1376406
           foreigners |   -.023782   .0364989    -0.65   0.516    -.0961292    .0485652
       pop_density_16 |   .0002171   .0001025     2.12   0.037     .0000139    .0004203
                _cons |   76.24734   2.056419    37.08   0.000     72.17116    80.32352
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,672
Absorbing 1 HDFE group                            F(  10,    108) =     123.73
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7142
                                                  Adj R-squared   =     0.7097
                                                  Within R-sq.    =     0.3438
Number of clusters (province_id) =        109     Root MSE        =     4.7015

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2085953   .0769011     2.71   0.008     .0561639    .3610266
             m5s_c_13 |   .2435437   .0517196     4.71   0.000     .1410265    .3460609
              pd_c_13 |  -.5104488   .0340129   -15.01   0.000    -.5778683   -.4430293
           turnout_13 |   .0007044   .0362669     0.02   0.985    -.0711828    .0725916
               income |  -.0004769   .0000948    -5.03   0.000    -.0006648    -.000289
         unemployment |    .177011   .0271871     6.51   0.000     .1231214    .2309006
           university |  -.2604903   .0583271    -4.47   0.000    -.3761048   -.1448758
               no_edu |  -.1866234   .0227186    -8.21   0.000    -.2316555   -.1415913
           foreigners |  -.0242201   .0368926    -0.66   0.513    -.0973477    .0489075
       pop_density_16 |   .0002166   .0001025     2.11   0.037     .0000134    .0004199
                _cons |   76.55459   2.087253    36.68   0.000     72.41729    80.69188
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,668
Absorbing 1 HDFE group                            F(  10,    108) =     124.63
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7133
                                                  Adj R-squared   =     0.7088
                                                  Within R-sq.    =     0.3431
Number of clusters (province_id) =        109     Root MSE        =     4.7149

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2020508   .0763383     2.65   0.009      .050735    .3533666
             m5s_c_13 |   .2454132   .0515428     4.76   0.000     .1432463    .3475801
              pd_c_13 |  -.5131754   .0334803   -15.33   0.000    -.5795392   -.4468116
           turnout_13 |   .0031682   .0358135     0.09   0.930    -.0678203    .0741567
               income |  -.0004923   .0001032    -4.77   0.000    -.0006968   -.0002877
         unemployment |   .1777955   .0273202     6.51   0.000     .1236421    .2319489
           university |  -.2464961   .0587279    -4.20   0.000    -.3629051   -.1300872
               no_edu |  -.1823404   .0227775    -8.01   0.000    -.2274894   -.1371915
           foreigners |  -.0234095   .0371781    -0.63   0.530     -.097103     .050284
       pop_density_16 |   .0002476   .0000984     2.52   0.013     .0000526    .0004426
                _cons |   76.33854   2.174318    35.11   0.000     72.02866    80.64841
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,760
Absorbing 1 HDFE group                            F(  10,    108) =     125.45
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7126
                                                  Adj R-squared   =     0.7081
                                                  Within R-sq.    =     0.3444
Number of clusters (province_id) =        109     Root MSE        =     4.6993

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2042098    .076943     2.65   0.009     .0516955    .3567241
             m5s_c_13 |   .2456401   .0515283     4.77   0.000     .1435021    .3477781
              pd_c_13 |  -.5130622   .0336163   -15.26   0.000    -.5796955   -.4464288
           turnout_13 |   .0035803   .0357805     0.10   0.920    -.0673428    .0745033
               income |   -.000479   .0000943    -5.08   0.000    -.0006659   -.0002921
         unemployment |    .177798   .0270969     6.56   0.000     .1240873    .2315088
           university |   -.257796   .0577284    -4.47   0.000    -.3722237   -.1433684
               no_edu |  -.1832287   .0227528    -8.05   0.000    -.2283287   -.1381288
           foreigners |  -.0230684   .0365672    -0.63   0.529    -.0955508    .0494141
       pop_density_16 |   .0002167   .0001026     2.11   0.037     .0000134      .00042
                _cons |   76.25588   2.056915    37.07   0.000     72.17871    80.33304
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,733
Absorbing 1 HDFE group                            F(  10,    108) =     125.00
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7141
                                                  Adj R-squared   =     0.7097
                                                  Within R-sq.    =     0.3453
Number of clusters (province_id) =        109     Root MSE        =     4.6879

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2046389   .0763555     2.68   0.009     .0532891    .3559887
             m5s_c_13 |   .2480661   .0517003     4.80   0.000     .1455872     .350545
              pd_c_13 |  -.5110155   .0337307   -15.15   0.000    -.5778755   -.4441554
           turnout_13 |   .0009683   .0360353     0.03   0.979    -.0704598    .0723965
               income |  -.0004889   .0000977    -5.01   0.000    -.0006825   -.0002953
         unemployment |   .1777817   .0273493     6.50   0.000     .1235706    .2319927
           university |  -.2536306   .0585712    -4.33   0.000    -.3697289   -.1375323
               no_edu |  -.1831285   .0229808    -7.97   0.000    -.2286805   -.1375766
           foreigners |  -.0223793   .0368486    -0.61   0.545    -.0954197     .050661
       pop_density_16 |   .0002139   .0001026     2.08   0.039     .0000105    .0004172
                _cons |     76.477    2.09276    36.54   0.000     72.32879    80.62521
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,728
Absorbing 1 HDFE group                            F(  10,    108) =     127.32
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7157
                                                  Adj R-squared   =     0.7113
                                                  Within R-sq.    =     0.3474
Number of clusters (province_id) =        109     Root MSE        =     4.6733

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |    .204164    .076304     2.68   0.009     .0529161    .3554118
             m5s_c_13 |    .247104    .051946     4.76   0.000      .144138      .35007
              pd_c_13 |  -.5083588   .0336125   -15.12   0.000    -.5749846    -.441733
           turnout_13 |   -.004089   .0354367    -0.12   0.908    -.0743307    .0661527
               income |  -.0004851   .0000949    -5.11   0.000    -.0006732    -.000297
         unemployment |   .1792303   .0272032     6.59   0.000     .1253088    .2331519
           university |    -.25984   .0584518    -4.45   0.000    -.3757016   -.1439785
               no_edu |  -.1885126   .0221302    -8.52   0.000    -.2323784   -.1446468
           foreigners |  -.0254821   .0368782    -0.69   0.491    -.0985811     .047617
       pop_density_16 |   .0002089   .0001017     2.05   0.042     7.35e-06    .0004104
                _cons |   76.99525    1.96091    39.27   0.000     73.10839    80.88212
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,706
Absorbing 1 HDFE group                            F(  10,    108) =     124.61
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7130
                                                  Adj R-squared   =     0.7086
                                                  Within R-sq.    =     0.3446
Number of clusters (province_id) =        109     Root MSE        =     4.6993

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2044151    .077117     2.65   0.009     .0515558    .3572745
             m5s_c_13 |   .2476931     .05181     4.78   0.000     .1449967    .3503895
              pd_c_13 |  -.5112293   .0337812   -15.13   0.000    -.5781895   -.4442691
           turnout_13 |   .0007795   .0358956     0.02   0.983    -.0703718    .0719308
               income |  -.0004714   .0000954    -4.94   0.000    -.0006606   -.0002822
         unemployment |   .1770887   .0270388     6.55   0.000      .123493    .2306843
           university |  -.2547846   .0579108    -4.40   0.000     -.369574   -.1399953
               no_edu |  -.1844098   .0227792    -8.10   0.000    -.2295621   -.1392576
           foreigners |  -.0229144   .0370669    -0.62   0.538    -.0963874    .0505585
       pop_density_16 |   .0002159   .0001027     2.10   0.038     .0000123    .0004196
                _cons |   76.32255   2.059529    37.06   0.000     72.24021     80.4049
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,754
Absorbing 1 HDFE group                            F(  10,    108) =     124.71
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7155
                                                  Adj R-squared   =     0.7111
                                                  Within R-sq.    =     0.3467
Number of clusters (province_id) =        109     Root MSE        =     4.6675

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2061693   .0760997     2.71   0.008     .0553264    .3570122
             m5s_c_13 |   .2449382   .0517858     4.73   0.000     .1422898    .3475865
              pd_c_13 |  -.5124375   .0337728   -15.17   0.000     -.579381    -.445494
           turnout_13 |  -.0000529    .035863    -0.00   0.999    -.0711396    .0710339
               income |  -.0004735   .0000942    -5.03   0.000    -.0006602   -.0002869
         unemployment |    .179707   .0276203     6.51   0.000     .1249587    .2344552
           university |  -.2647062   .0576027    -4.60   0.000    -.3788848   -.1505276
               no_edu |  -.1838908   .0228423    -8.05   0.000    -.2291683   -.1386133
           foreigners |  -.0259966   .0366589    -0.71   0.480    -.0986608    .0466677
       pop_density_16 |   .0002131   .0001022     2.09   0.039     .0000106    .0004156
                _cons |    76.5548   2.049112    37.36   0.000     72.49311     80.6165
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,684
Absorbing 1 HDFE group                            F(  10,    108) =     125.05
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7118
                                                  Adj R-squared   =     0.7073
                                                  Within R-sq.    =     0.3438
Number of clusters (province_id) =        109     Root MSE        =     4.7107

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2050614   .0765173     2.68   0.009     .0533908     .356732
             m5s_c_13 |   .2495281   .0517538     4.82   0.000     .1469431     .352113
              pd_c_13 |  -.5116278   .0338375   -15.12   0.000    -.5786995   -.4445561
           turnout_13 |     .00474   .0359556     0.13   0.895    -.0665302    .0760102
               income |  -.0004795   .0000956    -5.02   0.000    -.0006689   -.0002901
         unemployment |   .1780433    .027274     6.53   0.000     .1239814    .2321052
           university |  -.2532698   .0579725    -4.37   0.000    -.3681813   -.1383582
               no_edu |  -.1812696   .0227886    -7.95   0.000    -.2264406   -.1360986
           foreigners |  -.0195928   .0370783    -0.53   0.598    -.0930884    .0539029
       pop_density_16 |   .0002264   .0001022     2.22   0.029     .0000238     .000429
                _cons |   75.91251   2.056676    36.91   0.000     71.83582     79.9892
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,744
Absorbing 1 HDFE group                            F(  10,    108) =     123.44
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7124
                                                  Adj R-squared   =     0.7080
                                                  Within R-sq.    =     0.3426
Number of clusters (province_id) =        109     Root MSE        =     4.6984

                                   (Std. err. adjusted for 109 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2159504   .0772334     2.80   0.006     .0628603    .3690405
             m5s_c_13 |   .2480052    .051554     4.81   0.000     .1458163    .3501942
              pd_c_13 |  -.5116595   .0336527   -15.20   0.000    -.5783651   -.4449539
           turnout_13 |   .0030095   .0358062     0.08   0.933    -.0679645    .0739836
               income |    -.00048   .0000944    -5.09   0.000    -.0006671   -.0002929
         unemployment |   .1764472   .0271195     6.51   0.000     .1226916    .2302027
           university |  -.2588499   .0577957    -4.48   0.000     -.373411   -.1442887
               no_edu |  -.1824605   .0229462    -7.95   0.000     -.227944   -.1369771
           foreigners |  -.0224742   .0366836    -0.61   0.541    -.0951875    .0502391
       pop_density_16 |   .0002152   .0001029     2.09   0.039     .0000113    .0004191
                _cons |   76.22916   2.061255    36.98   0.000     72.14339    80.31492
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       109         109           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

.         * coefplot:
.         
.         coefplot pro*, ///
>         keep(std_wn_treat_campaign) ///
>         vertical ///
>         yline(0) pstyle(p1) ///
>         legend(off) xlabel("") /// 
>         ciopts(lwidth(0.4 ..)) mlwidth(medthick) msize(medsmall) mfcolor(white) ///
>         xtitle("{bf:jackknife:} province (1-110)") ///
>         ytitle("OLS coefficient of M5S rsvps on {bf:Referendum: No}") /// 
>         addplot(pcarrowi .43 1.275 .37 1.275 (12) "{it:Roma} dropped", mlabel(mlabcolor(uzhred2)) col(uzhred2))

. 
.         *save as pdf: 
.         graph export "$figures/figa2_jackknife.pdf", replace
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/figa2_jackknife.pdf saved as PDF format

.         
. 
.         // placebo tests (fig a3)
.         * estimate: 
.         cls 

.         eststo clear 

.         foreach var of varlist std_wn_postref_m0_m1-std_wn_postref_m11_m12 std_wn_posttreat {
  2.                 eststo: reghdfe referendum_no `var' `controls' if m5s_ref_ever==0, absorb(province_id)  cluster(province_id) 
  3.         }
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,185
Absorbing 1 HDFE group                            F(  10,    109) =     111.73
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6934
                                                  Adj R-squared   =     0.6882
                                                  Within R-sq.    =     0.3325
Number of clusters (province_id) =        110     Root MSE        =     4.7989

                                  (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------------
                     |               Robust
       referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_wn_postref_m0_m1 |   .0567757   .5663321     0.10   0.920    -1.065676    1.179228
            m5s_c_13 |   .2393398   .0471916     5.07   0.000     .1458076     .332872
             pd_c_13 |  -.5142311   .0315392   -16.30   0.000    -.5767408   -.4517214
          turnout_13 |   .0106832   .0340002     0.31   0.754    -.0567042    .0780706
              income |  -.0004587   .0001007    -4.56   0.000    -.0006583   -.0002592
        unemployment |   .1778965   .0283825     6.27   0.000     .1216434    .2341497
          university |  -.2824618   .0592774    -4.77   0.000    -.3999478   -.1649758
              no_edu |   -.178255   .0221844    -8.04   0.000    -.2222238   -.1342862
          foreigners |  -.0238033   .0350604    -0.68   0.499    -.0932919    .0456852
      pop_density_16 |   .0002012   .0001535     1.31   0.193     -.000103    .0005054
               _cons |   75.57429   2.110688    35.81   0.000     71.39097     79.7576
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est1 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,185
Absorbing 1 HDFE group                            F(  10,    109) =     110.66
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6934
                                                  Adj R-squared   =     0.6882
                                                  Within R-sq.    =     0.3325
Number of clusters (province_id) =        110     Root MSE        =     4.7987

                                  (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------------
                     |               Robust
       referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_wn_postref_m1_m2 |    1.36356   1.264096     1.08   0.283    -1.141836    3.868957
            m5s_c_13 |   .2391868   .0471935     5.07   0.000     .1456507    .3327229
             pd_c_13 |  -.5140623   .0315432   -16.30   0.000    -.5765799   -.4515448
          turnout_13 |    .010786   .0339941     0.32   0.752    -.0565893    .0781613
              income |  -.0004587   .0001007    -4.56   0.000    -.0006582   -.0002592
        unemployment |   .1782417      .0284     6.28   0.000     .1219538    .2345295
          university |  -.2826702   .0592386    -4.77   0.000    -.4000792   -.1652612
              no_edu |  -.1782128   .0221858    -8.03   0.000    -.2221842   -.1342413
          foreigners |  -.0241039   .0350701    -0.69   0.493    -.0936117     .045404
      pop_density_16 |   .0002012   .0001534     1.31   0.193    -.0001029    .0005052
               _cons |   75.56315   2.110252    35.81   0.000     71.38069     79.7456
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est2 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,185
Absorbing 1 HDFE group                            F(  10,    109) =     110.79
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6934
                                                  Adj R-squared   =     0.6883
                                                  Within R-sq.    =     0.3326
Number of clusters (province_id) =        110     Root MSE        =     4.7985

                                  (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------------
                     |               Robust
       referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_wn_postref_m2_m3 |   1.397549     .99291     1.41   0.162    -.5703667    3.365464
            m5s_c_13 |   .2392045   .0471979     5.07   0.000     .1456599    .3327492
             pd_c_13 |  -.5141155   .0315378   -16.30   0.000    -.5766225   -.4516086
          turnout_13 |   .0109249   .0340145     0.32   0.749    -.0564908    .0783406
              income |  -.0004581   .0001007    -4.55   0.000    -.0006576   -.0002586
        unemployment |   .1781732   .0283918     6.28   0.000     .1219016    .2344447
          university |  -.2834093   .0592151    -4.79   0.000    -.4007717    -.166047
              no_edu |  -.1781158   .0221838    -8.03   0.000    -.2220833   -.1341483
          foreigners |  -.0239672   .0350549    -0.68   0.496    -.0934448    .0455104
      pop_density_16 |   .0002013   .0001534     1.31   0.192    -.0001027    .0005054
               _cons |   75.54675   2.111987    35.77   0.000     71.36086    79.73264
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est3 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,185
Absorbing 1 HDFE group                            F(  10,    109) =     111.20
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6934
                                                  Adj R-squared   =     0.6882
                                                  Within R-sq.    =     0.3325
Number of clusters (province_id) =        110     Root MSE        =     4.7989

                                  (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------------
                     |               Robust
       referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_wn_postref_m3_m4 |   .4713756   .5617953     0.84   0.403    -.6420844    1.584836
            m5s_c_13 |   .2392662   .0472077     5.07   0.000      .145702    .3328303
             pd_c_13 |  -.5141899    .031537   -16.30   0.000    -.5766952   -.4516846
          turnout_13 |   .0107189   .0339906     0.32   0.753    -.0566494    .0780873
              income |  -.0004584   .0001007    -4.55   0.000    -.0006579   -.0002589
        unemployment |   .1779375   .0283744     6.27   0.000     .1217004    .2341747
          university |  -.2826857   .0592669    -4.77   0.000    -.4001508   -.1652206
              no_edu |  -.1782166   .0221855    -8.03   0.000    -.2221875   -.1342457
          foreigners |  -.0238798   .0350559    -0.68   0.497    -.0933594    .0455998
      pop_density_16 |   .0002008   .0001535     1.31   0.194    -.0001036    .0005051
               _cons |   75.56812   2.110712    35.80   0.000     71.38476    79.75149
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est4 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,185
Absorbing 1 HDFE group                            F(  10,    109) =     111.10
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6934
                                                  Adj R-squared   =     0.6882
                                                  Within R-sq.    =     0.3325
Number of clusters (province_id) =        110     Root MSE        =     4.7987

                                  (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------------
                     |               Robust
       referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_wn_postref_m4_m5 |   1.331816   1.271488     1.05   0.297    -1.188233    3.851864
            m5s_c_13 |   .2393928   .0471804     5.07   0.000     .1458828    .3329028
             pd_c_13 |   -.514247   .0315317   -16.31   0.000    -.5767418   -.4517522
          turnout_13 |   .0106465   .0339921     0.31   0.755    -.0567246    .0780177
              income |  -.0004582   .0001006    -4.55   0.000    -.0006577   -.0002588
        unemployment |   .1778822   .0283951     6.26   0.000     .1216041    .2341604
          university |  -.2831629   .0592097    -4.78   0.000    -.4005146   -.1658111
              no_edu |  -.1781484   .0221936    -8.03   0.000    -.2221355   -.1341614
          foreigners |  -.0240064   .0350707    -0.68   0.495    -.0935155    .0455026
      pop_density_16 |   .0002002   .0001537     1.30   0.196    -.0001045    .0005048
               _cons |   75.57181   2.111265    35.79   0.000     71.38735    79.75627
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est5 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,185
Absorbing 1 HDFE group                            F(  10,    109) =     111.18
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6934
                                                  Adj R-squared   =     0.6882
                                                  Within R-sq.    =     0.3325
Number of clusters (province_id) =        110     Root MSE        =     4.7987

                                  (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------------
                     |               Robust
       referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_wn_postref_m5_m6 |   1.590154    1.14976     1.38   0.169    -.6886328     3.86894
            m5s_c_13 |   .2393415   .0472038     5.07   0.000      .145785    .3328979
             pd_c_13 |  -.5141174   .0315312   -16.31   0.000    -.5766113   -.4516235
          turnout_13 |   .0108353   .0339982     0.32   0.751    -.0565481    .0782186
              income |  -.0004586   .0001007    -4.56   0.000    -.0006582   -.0002591
        unemployment |   .1779819   .0283779     6.27   0.000     .1217379    .2342259
          university |  -.2835389    .059313    -4.78   0.000    -.4010954   -.1659824
              no_edu |  -.1781668   .0221861    -8.03   0.000     -.222139   -.1341946
          foreigners |  -.0240353     .03507    -0.69   0.495    -.0935429    .0454724
      pop_density_16 |   .0001992   .0001537     1.30   0.198    -.0001056    .0005039
               _cons |   75.56296    2.10997    35.81   0.000     71.38107    79.74486
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est6 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,185
Absorbing 1 HDFE group                            F(  10,    109) =     111.51
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6934
                                                  Adj R-squared   =     0.6882
                                                  Within R-sq.    =     0.3325
Number of clusters (province_id) =        110     Root MSE        =     4.7989

                                  (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------------
                     |               Robust
       referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_wn_postref_m6_m7 |   -.067636   .6026064    -0.11   0.911    -1.261982     1.12671
            m5s_c_13 |   .2393418   .0471955     5.07   0.000     .1458018    .3328818
             pd_c_13 |  -.5142384   .0315432   -16.30   0.000    -.5767561   -.4517207
          turnout_13 |   .0106847   .0339997     0.31   0.754    -.0567016    .0780709
              income |  -.0004588   .0001007    -4.56   0.000    -.0006583   -.0002592
        unemployment |   .1778934   .0283815     6.27   0.000     .1216422    .2341446
          university |  -.2824203   .0593302    -4.76   0.000    -.4000108   -.1648298
              no_edu |  -.1782609   .0221922    -8.03   0.000    -.2222451   -.1342766
          foreigners |  -.0237854   .0350556    -0.68   0.499    -.0932645    .0456936
      pop_density_16 |   .0002012   .0001535     1.31   0.193    -.0001029    .0005054
               _cons |    75.5745   2.110941    35.80   0.000     71.39069    79.75832
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est7 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,185
Absorbing 1 HDFE group                            F(  10,    109) =     110.43
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6934
                                                  Adj R-squared   =     0.6882
                                                  Within R-sq.    =     0.3325
Number of clusters (province_id) =        110     Root MSE        =     4.7988

                                  (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------------
                     |               Robust
       referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_wn_postref_m7_m8 |   .7604057   1.101407     0.69   0.491    -1.422548    2.943359
            m5s_c_13 |   .2391316   .0472162     5.06   0.000     .1455507    .3327125
             pd_c_13 |  -.5141286   .0315411   -16.30   0.000    -.5766421    -.451615
          turnout_13 |   .0107109   .0339976     0.32   0.753    -.0566711     .078093
              income |  -.0004584   .0001007    -4.55   0.000    -.0006579   -.0002589
        unemployment |   .1780239   .0283994     6.27   0.000     .1217373    .2343106
          university |   -.282999    .059263    -4.78   0.000    -.4004562   -.1655417
              no_edu |  -.1783005   .0221856    -8.04   0.000    -.2222716   -.1343294
          foreigners |  -.0237581    .035037    -0.68   0.499    -.0932004    .0456842
      pop_density_16 |    .000201   .0001535     1.31   0.193    -.0001032    .0005053
               _cons |   75.57322   2.110342    35.81   0.000     71.39059    79.75585
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est8 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,185
Absorbing 1 HDFE group                            F(  10,    109) =     110.38
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6934
                                                  Adj R-squared   =     0.6882
                                                  Within R-sq.    =     0.3325
Number of clusters (province_id) =        110     Root MSE        =     4.7987

                                  (Std. err. adjusted for 110 clusters in province_id)
--------------------------------------------------------------------------------------
                     |               Robust
       referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
std_wn_postref_m8_m9 |    1.51937   1.804994     0.84   0.402     -2.05807    5.096811
            m5s_c_13 |   .2391227   .0472073     5.07   0.000     .1455593    .3326861
             pd_c_13 |  -.5141686   .0315275   -16.31   0.000    -.5766551    -.451682
          turnout_13 |   .0107344   .0340018     0.32   0.753     -.056656    .0781248
              income |   -.000458   .0001007    -4.55   0.000    -.0006575   -.0002585
        unemployment |   .1780523   .0283993     6.27   0.000     .1217657    .2343389
          university |  -.2837013   .0592789    -4.79   0.000    -.4011901   -.1662124
              no_edu |  -.1783253   .0221825    -8.04   0.000    -.2222902   -.1343604
          foreigners |  -.0235992    .035042    -0.67   0.502    -.0930513    .0458529
      pop_density_16 |   .0002018   .0001534     1.32   0.191    -.0001022    .0005058
               _cons |   75.57109   2.111033    35.80   0.000      71.3871    79.75509
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est9 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,185
Absorbing 1 HDFE group                            F(  10,    109) =     112.57
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6934
                                                  Adj R-squared   =     0.6882
                                                  Within R-sq.    =     0.3325
Number of clusters (province_id) =        110     Root MSE        =     4.7989

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_postref_m9_m10 |   .4554584   1.919949     0.24   0.813    -3.349819    4.260736
             m5s_c_13 |    .239297   .0472014     5.07   0.000     .1457454    .3328486
              pd_c_13 |  -.5141611   .0315315   -16.31   0.000    -.5766556   -.4516666
           turnout_13 |   .0106629   .0339974     0.31   0.754     -.056719    .0780447
               income |  -.0004586   .0001007    -4.56   0.000    -.0006581   -.0002591
         unemployment |   .1780137   .0284154     6.26   0.000     .1216953    .2343321
           university |  -.2827586   .0594504    -4.76   0.000    -.4005873     -.16493
               no_edu |   -.178282   .0221869    -8.04   0.000    -.2222556   -.1343083
           foreigners |  -.0237823   .0350383    -0.68   0.499     -.093227    .0456625
       pop_density_16 |   .0002008   .0001536     1.31   0.194    -.0001036    .0005053
                _cons |   75.57473   2.110248    35.81   0.000     71.39229    79.75717
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est10 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,185
Absorbing 1 HDFE group                            F(  10,    109) =     110.29
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6934
                                                  Adj R-squared   =     0.6882
                                                  Within R-sq.    =     0.3325
Number of clusters (province_id) =        110     Root MSE        =     4.7988

                                    (Std. err. adjusted for 110 clusters in province_id)
----------------------------------------------------------------------------------------
                       |               Robust
         referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------+----------------------------------------------------------------
std_wn_postref_m10_m11 |   .7082573   1.068266     0.66   0.509    -1.409012    2.825526
              m5s_c_13 |   .2392517   .0472137     5.07   0.000     .1456756    .3328278
               pd_c_13 |  -.5141374   .0315325   -16.30   0.000    -.5766339   -.4516409
            turnout_13 |    .010831   .0340108     0.32   0.751    -.0565772    .0782393
                income |  -.0004586   .0001007    -4.55   0.000    -.0006582    -.000259
          unemployment |   .1778442   .0283541     6.27   0.000     .1216473    .2340411
            university |  -.2826498   .0592836    -4.77   0.000    -.4001479   -.1651517
                no_edu |  -.1781268   .0222059    -8.02   0.000    -.2221382   -.1341153
            foreigners |  -.0237964   .0350399    -0.68   0.498    -.0932444    .0456515
        pop_density_16 |   .0001997   .0001532     1.30   0.195    -.0001039    .0005033
                 _cons |   75.55794   2.112537    35.77   0.000     71.37096    79.74492
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est11 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,185
Absorbing 1 HDFE group                            F(  10,    109) =     110.33
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6934
                                                  Adj R-squared   =     0.6882
                                                  Within R-sq.    =     0.3325
Number of clusters (province_id) =        110     Root MSE        =     4.7989

                                    (Std. err. adjusted for 110 clusters in province_id)
----------------------------------------------------------------------------------------
                       |               Robust
         referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------+----------------------------------------------------------------
std_wn_postref_m11_m12 |   -.060554   .4271256    -0.14   0.888    -.9071032    .7859951
              m5s_c_13 |   .2393624     .04722     5.07   0.000     .1457739     .332951
               pd_c_13 |   -.514241   .0315365   -16.31   0.000    -.5767452   -.4517368
            turnout_13 |   .0106702   .0339973     0.31   0.754    -.0567113    .0780517
                income |  -.0004588   .0001007    -4.56   0.000    -.0006583   -.0002592
          unemployment |   .1778704   .0283978     6.26   0.000     .1215869     .234154
            university |  -.2824015   .0593625    -4.76   0.000     -.400056   -.1647469
                no_edu |  -.1782577   .0221859    -8.03   0.000    -.2222295    -.134286
            foreigners |   -.023788   .0350497    -0.68   0.499    -.0932555    .0456794
        pop_density_16 |   .0002013   .0001534     1.31   0.192    -.0001026    .0005053
                 _cons |   75.57521   2.110376    35.81   0.000     71.39251     79.7579
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est12 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,185
Absorbing 1 HDFE group                            F(  10,    109) =     112.54
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6934
                                                  Adj R-squared   =     0.6882
                                                  Within R-sq.    =     0.3325
Number of clusters (province_id) =        110     Root MSE        =     4.7987

                              (Std. err. adjusted for 110 clusters in province_id)
----------------------------------------------------------------------------------
                 |               Robust
   referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
std_wn_posttreat |   .1874014   .1810689     1.03   0.303    -.1714713     .546274
        m5s_c_13 |   .2391057   .0472451     5.06   0.000     .1454675    .3327439
         pd_c_13 |   -.513939   .0315102   -16.31   0.000    -.5763913   -.4514868
      turnout_13 |   .0107621   .0339858     0.32   0.752    -.0565966    .0781208
          income |  -.0004582   .0001007    -4.55   0.000    -.0006578   -.0002586
    unemployment |   .1781156    .028401     6.27   0.000     .1218257    .2344055
      university |  -.2837245    .059464    -4.77   0.000    -.4015802   -.1658688
          no_edu |  -.1780123    .022168    -8.03   0.000    -.2219486    -.134076
      foreigners |  -.0239757   .0350725    -0.68   0.496    -.0934881    .0455368
  pop_density_16 |    .000199   .0001533     1.30   0.197    -.0001048    .0005028
           _cons |   75.55588   2.107062    35.86   0.000     71.37975    79.73201
----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est13 stored)

.         * coefplot:
.         coefplot ///
>         (est1, mlabels(std_wn_postref_m0_m1 = 1 "{bf:01/2017}") pstyle(p1)) ///
>         (est2, pstyle(p1)) ///
>         (est3, pstyle(p1)) ///
>         (est4, pstyle(p1)) ///
>         (est5, pstyle(p1)) ///
>         (est6, pstyle(p1) mlabels(std_wn_postref_m5_m6 = 1 "{bf:06/2017}")) ///
>         (est7, pstyle(p1)) ///
>         (est8, pstyle(p1)) ///
>         (est9, pstyle(p1)) ///
>         (est10, pstyle(p1)) ///
>         (est11, pstyle(p1)) /// 
>         (est12, mlabels(std_wn_postref_m11_m12 = 11 "{bf:12/2017}") pstyle(p1)) ///
>         (est13, msymbol(D) mlabels(std_wn_posttreat = 11 "{&sum} 2017") pstyle(p2)) ///
>         , rename(std_wn_postref* = postref*) vertical legend(off) ///
>         xlabel("") yline(0) ytitle("OLS coefficient of [...] on {bf:Referendum: No}") ///
>         drop(_cons `controls') ///
>         ciopts(lwidth(0.4 ..)) mlwidth(medthick) msize(medsmall) mfcolor(white) 

.         * save as pdf: 
.         graph export "$figures/figa3_placebos.pdf", replace
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/figa3_placebos.pdf saved as PDF format

.         
.         // different campaign period (tab a4)
.         cls

.         eststo clear

.         eststo: reghdfe referendum_no m5s_ref_ever_short, noabsorb cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       4.64
Statistics robust to heteroskedasticity           Prob > F        =     0.0335
                                                  R-squared       =     0.0053
                                                  Adj R-squared   =     0.0052
                                                  Within R-sq.    =     0.0053
Number of clusters (province_id) =        110     Root MSE        =     8.7243

                                (Std. err. adjusted for 110 clusters in province_id)
------------------------------------------------------------------------------------
                   |               Robust
     referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
m5s_ref_ever_short |    2.51747   1.168804     2.15   0.033     .2009388    4.834002
             _cons |   59.34747   .6602326    89.89   0.000     58.03891    60.65603
------------------------------------------------------------------------------------
(est1 stored)

.         eststo: reghdfe referendum_no m5s_ref_ever_short, absorb(province_id) cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       6.61
Statistics robust to heteroskedasticity           Prob > F        =     0.0115
                                                  R-squared       =     0.5572
                                                  Adj R-squared   =     0.5510
                                                  Within R-sq.    =     0.0014
Number of clusters (province_id) =        110     Root MSE        =     5.8611

                                (Std. err. adjusted for 110 clusters in province_id)
------------------------------------------------------------------------------------
                   |               Robust
     referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
m5s_ref_ever_short |   .9205465   .3579685     2.57   0.011     .2110646    1.630028
             _cons |   59.45774   .0247184  2405.41   0.000     59.40875    59.50673
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est2 stored)

.         eststo: reghdfe referendum_no m5s_ref_ever_short `controls', absorb(province_id)  cluster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  10,    109) =     127.63
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7128
                                                  Adj R-squared   =     0.7083
                                                  Within R-sq.    =     0.3454
Number of clusters (province_id) =        110     Root MSE        =     4.6878

                                (Std. err. adjusted for 110 clusters in province_id)
------------------------------------------------------------------------------------
                   |               Robust
     referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
m5s_ref_ever_short |    .695998   .1899895     3.66   0.000     .3194449    1.072551
          m5s_c_13 |   .2469072   .0511394     4.83   0.000     .1455506    .3482639
           pd_c_13 |  -.5134605   .0334501   -15.35   0.000    -.5797575   -.4471635
        turnout_13 |   .0037748   .0355581     0.11   0.916    -.0667001    .0742497
            income |  -.0004769   .0000941    -5.07   0.000    -.0006633   -.0002904
      unemployment |   .1771413   .0270152     6.56   0.000      .123598    .2306846
        university |  -.2622361   .0572615    -4.58   0.000    -.3757265   -.1487456
            no_edu |  -.1823093   .0226869    -8.04   0.000    -.2272739   -.1373446
        foreigners |  -.0237979   .0363729    -0.65   0.514    -.0958877     .048292
    pop_density_16 |   .0001977   .0001064     1.86   0.066    -.0000132    .0004087
             _cons |   76.22186   2.055979    37.07   0.000     72.14698    80.29675
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est3 stored)

.         ebalance m5s_ref_ever_short `controls'


Data Setup
Treatment variable:   m5s_ref_ever_short
Covariate adjustment: m5s_c_13 pd_c_13 turnout_13 income unemployment university no_edu foreigners pop_density_16 

Optimizing...
Iteration 1: Max Difference = 54193.6554
Iteration 2: Max Difference = 19934.7597
Iteration 3: Max Difference = 7331.6174
Iteration 4: Max Difference = 2695.18354
Iteration 5: Max Difference = 989.543202
Iteration 6: Max Difference = 362.095701
Iteration 7: Max Difference = 131.330397
Iteration 8: Max Difference = 46.5881377
Iteration 9: Max Difference = 15.7504302
Iteration 10: Max Difference = 4.97938853
Iteration 11: Max Difference = 1.56164863
Iteration 12: Max Difference = .368963889
Iteration 13: Max Difference = .027657188
Iteration 14: Max Difference = .000156039
maximum difference smaller than the tolerance level; convergence achieved


Treated units: 549     total of weights: 549
Control units: 7259    total of weights: 549


Before: without weighting

             |              Treat              |             Control             
             |      mean   variance   skewness |      mean   variance   skewness 
-------------+---------------------------------+---------------------------------
    m5s_c_13 |     20.76      21.16      .2277 |     18.32      35.06     .03086 
     pd_c_13 |     19.56      54.36      1.061 |      18.6      42.14      .7038 
  turnout_13 |     74.65      48.22     -.7575 |     74.67      61.71     -.9541 
      income |     11961   1.22e+07      .1829 |     11995    9098570     .05505 
unemployment |     13.26      45.82      .7321 |      10.1      38.84      1.251 
  university |     9.449      12.74      1.066 |     6.921      5.678       1.15 
      no_edu |     28.39      30.44      .7335 |     33.62      57.04      1.063 
  foreigners |     7.444      21.44      .5736 |     6.567       19.5      1.007 
pop_densi~16 |     903.7    1703204      3.627 |     264.2     310303       7.91 


After:  _webal as the weighting variable

             |              Treat              |             Control             
             |      mean   variance   skewness |      mean   variance   skewness 
-------------+---------------------------------+---------------------------------
    m5s_c_13 |     20.76      21.16      .2277 |     20.76      30.49      .2164 
     pd_c_13 |     19.56      54.36      1.061 |     19.56       38.3      .8062 
  turnout_13 |     74.65      48.22     -.7575 |     74.65      54.72     -.9111 
      income |     11961   1.22e+07      .1829 |     11961   1.44e+07      1.039 
unemployment |     13.26      45.82      .7321 |     13.26      56.18      .8203 
  university |     9.449      12.74      1.066 |     9.448      15.21      1.506 
      no_edu |     28.39      30.44      .7335 |     28.39      32.65      .5675 
  foreigners |     7.444      21.44      .5736 |     7.444      29.29      1.209 
pop_densi~16 |     903.7    1703204      3.627 |     903.6    3988030      4.103 

.         eststo: reghdfe referendum_no m5s_ref_ever_short [aweight=_webal], absorb(province_id)  cluster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(   1,    109) =       5.21
Statistics robust to heteroskedasticity           Prob > F        =     0.0244
                                                  R-squared       =     0.7318
                                                  Adj R-squared   =     0.7279
                                                  Within R-sq.    =     0.0021
Number of clusters (province_id) =        110     Root MSE        =     4.6431

                                (Std. err. adjusted for 110 clusters in province_id)
------------------------------------------------------------------------------------
                   |               Robust
     referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
m5s_ref_ever_short |   .4756738   .2083842     2.28   0.024     .0626631    .8886845
             _cons |   61.41186   .1042076   589.32   0.000     61.20532    61.61839
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est4 stored)

.         eststo: reghdfe referendum_no std_wn_treat_campaign_short, noabsorb cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       7.18
Statistics robust to heteroskedasticity           Prob > F        =     0.0085
                                                  R-squared       =     0.0067
                                                  Adj R-squared   =     0.0066
                                                  Within R-sq.    =     0.0067
Number of clusters (province_id) =        110     Root MSE        =     8.7183

                                         (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_treat_campaign_short |   1.584723   .5914533     2.68   0.009     .4124813    2.756964
                      _cons |   59.35223   .6616751    89.70   0.000     58.04081    60.66364
---------------------------------------------------------------------------------------------
(est5 stored)

.         eststo: reghdfe referendum_no std_wn_treat_campaign_short, absorb(province_id) cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       7.54
Statistics robust to heteroskedasticity           Prob > F        =     0.0071
                                                  R-squared       =     0.5572
                                                  Adj R-squared   =     0.5510
                                                  Within R-sq.    =     0.0013
Number of clusters (province_id) =        110     Root MSE        =     5.8613

                                         (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_treat_campaign_short |   .4974585   .1811341     2.75   0.007     .1384567    .8564604
                      _cons |   59.46823   .0193258  3077.14   0.000     59.42993    59.50653
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est6 stored)

.         eststo: reghdfe referendum_no std_wn_treat_campaign_short `controls', absorb(province_id)  cluster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  10,    109) =     126.19
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7126
                                                  Adj R-squared   =     0.7082
                                                  Within R-sq.    =     0.3451
Number of clusters (province_id) =        110     Root MSE        =     4.6888

                                         (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_treat_campaign_short |   .2995348   .1096371     2.73   0.007     .0822377    .5168318
                   m5s_c_13 |   .2470378   .0512784     4.82   0.000     .1454057    .3486699
                    pd_c_13 |  -.5132073   .0334637   -15.34   0.000    -.5795312   -.4468833
                 turnout_13 |   .0031771   .0357012     0.09   0.929    -.0675814    .0739357
                     income |  -.0004789   .0000942    -5.09   0.000    -.0006656   -.0002923
               unemployment |   .1779525   .0270713     6.57   0.000     .1242979     .231607
                 university |  -.2568111   .0577643    -4.45   0.000     -.371298   -.1423241
                     no_edu |  -.1829064   .0226964    -8.06   0.000      -.22789   -.1379229
                 foreigners |   -.023519   .0364829    -0.64   0.521    -.0958271     .048789
             pop_density_16 |   .0002189   .0001016     2.15   0.033     .0000174    .0004203
                      _cons |   76.26498   2.055325    37.11   0.000     72.19139    80.33857
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est7 stored)

.         eststo: reghdfe referendum_no std_wn_treat_campaign_short [aweight=_webal], absorb(province_id)  cluster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(   1,    109) =       5.54
Statistics robust to heteroskedasticity           Prob > F        =     0.0203
                                                  R-squared       =     0.7321
                                                  Adj R-squared   =     0.7283
                                                  Within R-sq.    =     0.0034
Number of clusters (province_id) =        110     Root MSE        =     4.6401

                                         (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_treat_campaign_short |   .3050285   .1295465     2.35   0.020     .0482714    .5617855
                      _cons |   61.41337   .1003835   611.79   0.000     61.21441    61.61232
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est8 stored)

.         ** create a LaTeX Table:
.         estfe est*, labels(province_id "Province FE")

.         ** save table: 
.         esttab est* using "$tables/taba4_shortercampaign.tex", replace  ///
>         indicate( `r(indicate_fe)' "Controls=income", labels(\checkmark)) ///
>         se nobaselevels nostar label se(2) b(2) ///
>         noconstant nogaps ///
>         drop(pd_c_13 turnout_13 unemployment university no_edu foreigners pop_density_16) ///
>         stats(N N_clust r2_a r2_a_within rmse, labels("Obs" "Provinces" "adj.R\$^2$" "adj.R\$^2$ (within)" "RMSE") fmt(%9.0f %9.0f
>  %9.2f %9.2f %9.2f)) ///
>         note("\emph{Note:} Clustered standard errors by province in parentheses. Controls omitted from table: PD: \% votes 2013, \
> % turnout 2013, income per cap, \% unemployed, \% university degree, \% low education, \% foreigners, population density. Same var
> iables used for matching, history omitted from matching.") ///
>         mgroups("Binary" "Continuous", pattern( 0 0 0 0 1 0 0 0 1) ///
>         prefix(\multicolumn{@span}{c}{) suffix(}) ///
>         span erepeat(\cmidrule(lr){@span})) ///
>         substitute(_ _) 
(output written to /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/tables/taba4_shortercampaign.tex)

. 
.         // Instrument 
. 
.                 * internet penetration across time (fig a4)
.                 project, original("$data_original/internet penetration across time/access_ts.dta")
project PlaceBased_analysis > do-file uses original: "data_original/internet penetration across time/access_ts.dta" filesig(42743367
> 73:2992)

. 
.                 use "$data_original/internet penetration across time/access_ts.dta", clear 

.                 * tw plot: 
.                 tw connected access year, ///
>                 xlabel(2007(1)2019) xline(2009) mfcolor(white) mlabel(access) ///
>                 mlabposition(11) ylab(, nogrid)

.                 * save as pdf: 
.                 graph export "$figures/figa4_access_ts.pdf", replace
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/figa4_access_ts.pdf saved as PDF format

. 
.                 * OLS of broadband with UGS distance (fig a5)
.                 use "$data_coded/placebased_regional.dta", clear 

.                 * estimate: 
.                 eststo clear 

.                 foreach var of varlist adsl12 adsl13 adsl14 adsl15 adsl18 {
  2.                         eststo: reghdfe `var' log_ugs, absorb(province_id) cluster(province_id)
  3.                 } 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,938
Absorbing 1 HDFE group                            F(   1,    109) =     124.62
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1812
                                                  Adj R-squared   =     0.1697
                                                  Within R-sq.    =     0.0511
Number of clusters (province_id) =        110     Root MSE        =    29.4621

                          (Std. err. adjusted for 110 clusters in province_id)
------------------------------------------------------------------------------
             |               Robust
      adsl12 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
     log_ugs |  -10.00173   .8959538   -11.16   0.000    -11.77749   -8.225983
       _cons |    103.912   2.245971    46.27   0.000     99.46058    108.3635
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est1 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,938
Absorbing 1 HDFE group                            F(   1,    109) =      99.93
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.2027
                                                  Adj R-squared   =     0.1915
                                                  Within R-sq.    =     0.0364
Number of clusters (province_id) =        110     Root MSE        =    24.7193

                          (Std. err. adjusted for 110 clusters in province_id)
------------------------------------------------------------------------------
             |               Robust
      adsl13 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
     log_ugs |  -7.029052   .7031507   -10.00   0.000    -8.422674    -5.63543
       _cons |   102.4493   1.762654    58.12   0.000     98.95581    105.9429
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est2 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,938
Absorbing 1 HDFE group                            F(   1,    109) =      78.88
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.2002
                                                  Adj R-squared   =     0.1889
                                                  Within R-sq.    =     0.0298
Number of clusters (province_id) =        110     Root MSE        =    23.5833

                          (Std. err. adjusted for 110 clusters in province_id)
------------------------------------------------------------------------------
             |               Robust
      adsl14 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
     log_ugs |  -6.041262   .6801981    -8.88   0.000    -7.389393   -4.693132
       _cons |   101.5158   1.705116    59.54   0.000     98.13636    104.8953
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est3 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,938
Absorbing 1 HDFE group                            F(   1,    109) =      24.47
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1326
                                                  Adj R-squared   =     0.1204
                                                  Within R-sq.    =     0.0113
Number of clusters (province_id) =        110     Root MSE        =     4.7744

                          (Std. err. adjusted for 110 clusters in province_id)
------------------------------------------------------------------------------
             |               Robust
      adsl15 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
     log_ugs |  -.7469362   .1510053    -4.95   0.000    -1.046224   -.4476487
       _cons |   100.1201    .378539   264.49   0.000     99.36985    100.8704
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est4 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,643
Absorbing 1 HDFE group                            F(   1,    105) =     311.93
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3748
                                                  Adj R-squared   =     0.3660
                                                  Within R-sq.    =     0.1153
Number of clusters (province_id) =        106     Root MSE        =     0.2849

                          (Std. err. adjusted for 106 clusters in province_id)
------------------------------------------------------------------------------
             |               Robust
      adsl18 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
     log_ugs |  -.1498287   .0084833   -17.66   0.000    -.1666495   -.1330078
       _cons |   .6362919   .0211295    30.11   0.000     .5943959    .6781879
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       106         106           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est5 stored)

.                 * coefplot:
.                 coefplot ///
>                 (est1,  mlabels(log_ugs = 3 "2012"))  ///
>                 (est2,  mlabels(log_ugs = 3 "2013"))  ///
>                 (est3,  mlabels(log_ugs = 3 "2014"))  ///
>                 (est4,  mlabels(log_ugs = 3 "2015"))  ///
>                 (est5,  mlabels(log_ugs = 3 "2018"))  ///
>                 , ///
>                 keep(log_ugs) vertical ///
>                 yline(0, lcol(black)) ///
>                 ciopts(lwidth(0.4 ..)) mlwidth(medthick) msize(medsmall) mfcolor(white) ///
>                 legend(off) xlabel("") ///
>                 ytitle("OLS coefficient of UGS distance on % population with broadband internet") 

.                 * save as pdf: 
.                 graph export "$figures/figa5_ugs_adsl.pdf", replace
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/figa5_ugs_adsl.pdf saved as PDF format

. 
.                 * Map of UGS distance (fig a6a)
.                 use "$data_coded/placebased_mapdata.dta", clear 

. 
.                 spmap km_to_ugs using "$data_coded/itcoord", ///
>                 id(id) ocolor(white ..) osize(none ..) ///
>                 clmethod(c) clbreaks(0 5 6 7 8 9 10 15 20 30 40 50) ///
>                 fcolor(BuRd) ///
>                 legtitle("{bf: Distance to closest UGS} {it:(in km)}") legend(pos(7)) legstyle(3) legcount 

.                 ***save as pdf: 
.                 graph export "$figures/figa6a_ugs.pdf", replace
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/figa6a_ugs.pdf saved as PDF format

. 
.                 * Map of UGS referendum no (fig a6b)
.                 use "$data_coded/placebased_mapdata.dta", clear 

. 
.                 spmap referendum_no using "$data_coded/itcoord", ///
>                 id(id) ocolor(white ..) osize(none ..) ///
>                 fcolor(BuRd) 

.                 ***save as pdf: 
.                 graph export "$figures/figa6b_referendum.pdf", replace
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/figa6b_referendum.pdf saved as PDF format

. 
.                 * Testing independence with ITANES 1996 (fig a8)
.                 use "$data_coded/placebased_independence.dta", clear
(Written by R)

.                 * define controls: 
.                 global controls age female education unemployed religiosity

.                 * estimate OLS on variable which might be correlated with internet:
.                 cls 

.                 eststo clear

.                 foreach var of varlist vote96maj_1 vote96maj_2 vote96maj_3 vote96pro_3 vote96pro_5 vote96pro_7 vote96pro_8 lr effi
> cacy_* dem_sat democrat econ_worse econ_worse_personal {
  2.                         fre `var'
  3.                         rename `var' independence
  4.                         eststo: reghdfe independence log_ugs population_2001 [pweight=weight], absorb(province_id) cluster(comu
> ne_id)
  5.                         rename independence `var'
  6.                 }

vote96maj_1 -- Ulivo (0,1)
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   0     |        911      36.41      46.29      46.29
        1     |       1057      42.25      53.71     100.00
        Total |       1968      78.66     100.00           
Missing .     |        534      21.34                      
Total         |       2502     100.00                      
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      1,844
Absorbing 1 HDFE group                            F(   2,    532) =       1.04
Statistics robust to heteroskedasticity           Prob > F        =     0.3529
                                                  R-squared       =     0.0538
                                                  Adj R-squared   =     0.0392
                                                  Within R-sq.    =     0.0016
Number of clusters (comune_id) =        533       Root MSE        =     0.4877

                               (Std. err. adjusted for 533 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |   .0168259   .0133927     1.26   0.210    -.0094832     .043135
population_2001 |   4.29e-08   3.41e-08     1.26   0.209    -2.41e-08    1.10e-07
          _cons |   .5162913   .0277565    18.60   0.000     .4617656     .570817
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est1 stored)

vote96maj_2 -- POL (0,1)
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   0     |       1218      48.68      61.89      61.89
        1     |        750      29.98      38.11     100.00
        Total |       1968      78.66     100.00           
Missing .     |        534      21.34                      
Total         |       2502     100.00                      
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      1,844
Absorbing 1 HDFE group                            F(   2,    532) =       1.78
Statistics robust to heteroskedasticity           Prob > F        =     0.1703
                                                  R-squared       =     0.0342
                                                  Adj R-squared   =     0.0193
                                                  Within R-sq.    =     0.0026
Number of clusters (comune_id) =        533       Root MSE        =     0.4751

                               (Std. err. adjusted for 533 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |  -.0220322   .0116965    -1.88   0.060    -.0450091    .0009447
population_2001 |  -2.95e-08   3.56e-08    -0.83   0.408    -9.94e-08    4.05e-08
          _cons |    .397688   .0248404    16.01   0.000     .3488906    .4464854
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est2 stored)

vote96maj_3 -- LN (0,1)
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   0     |       1851      73.98      94.05      94.05
        1     |        117       4.68       5.95     100.00
        Total |       1968      78.66     100.00           
Missing .     |        534      21.34                      
Total         |       2502     100.00                      
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      1,844
Absorbing 1 HDFE group                            F(   2,    532) =       2.82
Statistics robust to heteroskedasticity           Prob > F        =     0.0608
                                                  R-squared       =     0.1314
                                                  Adj R-squared   =     0.1180
                                                  Within R-sq.    =     0.0041
Number of clusters (comune_id) =        533       Root MSE        =     0.2287

                               (Std. err. adjusted for 533 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |   .0061456    .005637     1.09   0.276    -.0049279     .017219
population_2001 |  -2.98e-08   1.89e-08    -1.57   0.116    -6.70e-08    7.38e-09
          _cons |   .0606566   .0132103     4.59   0.000     .0347059    .0866073
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est3 stored)

vote96pro_3 -- PD 1996 (0,1)
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   0     |       1489      59.51      72.21      72.21
        1     |        573      22.90      27.79     100.00
        Total |       2062      82.41     100.00           
Missing .     |        440      17.59                      
Total         |       2502     100.00                      
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      1,933
Absorbing 1 HDFE group                            F(   2,    533) =       0.07
Statistics robust to heteroskedasticity           Prob > F        =     0.9302
                                                  R-squared       =     0.0727
                                                  Adj R-squared   =     0.0591
                                                  Within R-sq.    =     0.0001
Number of clusters (comune_id) =        534       Root MSE        =     0.4421

                               (Std. err. adjusted for 534 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |  -.0009943   .0125808    -0.08   0.937    -.0257083    .0237198
population_2001 |   8.32e-09   3.13e-08     0.27   0.791    -5.32e-08    6.99e-08
          _cons |   .2938065   .0259322    11.33   0.000     .2428646    .3447484
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est4 stored)

vote96pro_5 -- FI 1996 (0,1)
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   0     |       1704      68.11      82.64      82.64
        1     |        358      14.31      17.36     100.00
        Total |       2062      82.41     100.00           
Missing .     |        440      17.59                      
Total         |       2502     100.00                      
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      1,933
Absorbing 1 HDFE group                            F(   2,    533) =       0.68
Statistics robust to heteroskedasticity           Prob > F        =     0.5075
                                                  R-squared       =     0.0268
                                                  Adj R-squared   =     0.0125
                                                  Within R-sq.    =     0.0010
Number of clusters (comune_id) =        534       Root MSE        =     0.3809

                               (Std. err. adjusted for 534 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |  -.0104656   .0090225    -1.16   0.247    -.0281896    .0072583
population_2001 |  -1.03e-08   2.65e-08    -0.39   0.698    -6.22e-08    4.17e-08
          _cons |   .1967086   .0188581    10.43   0.000     .1596632     .233754
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est5 stored)

vote96pro_7 -- AN 1996 (0,1)
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   0     |       1741      69.58      84.43      84.43
        1     |        321      12.83      15.57     100.00
        Total |       2062      82.41     100.00           
Missing .     |        440      17.59                      
Total         |       2502     100.00                      
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      1,933
Absorbing 1 HDFE group                            F(   2,    533) =       0.78
Statistics robust to heteroskedasticity           Prob > F        =     0.4574
                                                  R-squared       =     0.0303
                                                  Adj R-squared   =     0.0160
                                                  Within R-sq.    =     0.0009
Number of clusters (comune_id) =        534       Root MSE        =     0.3456

                               (Std. err. adjusted for 534 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |   -.009262   .0074044    -1.25   0.212    -.0238075    .0052834
population_2001 |  -1.64e-08   3.14e-08    -0.52   0.601    -7.80e-08    4.52e-08
          _cons |   .1586436   .0180438     8.79   0.000     .1231979    .1940893
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est6 stored)

vote96pro_8 -- LN 1996 (0,1)
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   0     |       1904      76.10      92.34      92.34
        1     |        158       6.31       7.66     100.00
        Total |       2062      82.41     100.00           
Missing .     |        440      17.59                      
Total         |       2502     100.00                      
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      1,933
Absorbing 1 HDFE group                            F(   2,    533) =       2.15
Statistics robust to heteroskedasticity           Prob > F        =     0.1171
                                                  R-squared       =     0.1233
                                                  Adj R-squared   =     0.1104
                                                  Within R-sq.    =     0.0029
Number of clusters (comune_id) =        534       Root MSE        =     0.2636

                               (Std. err. adjusted for 534 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |   .0060464   .0067725     0.89   0.372    -.0072578    .0193505
population_2001 |  -2.95e-08   2.11e-08    -1.40   0.163    -7.10e-08    1.20e-08
          _cons |   .0827125   .0152123     5.44   0.000     .0528291    .1125959
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est7 stored)

lr -- left-right self (1-5)
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   1     |        526      21.02      23.07      23.07
        2     |        668      26.70      29.30      52.37
        3     |        313      12.51      13.73      66.10
        4     |        506      20.22      22.19      88.29
        5     |        267      10.67      11.71     100.00
        Total |       2280      91.13     100.00           
Missing .     |        222       8.87                      
Total         |       2502     100.00                      
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      2,134
Absorbing 1 HDFE group                            F(   2,    551) =       0.35
Statistics robust to heteroskedasticity           Prob > F        =     0.7014
                                                  R-squared       =     0.0455
                                                  Adj R-squared   =     0.0328
                                                  Within R-sq.    =     0.0003
Number of clusters (comune_id) =        552       Root MSE        =     1.3480

                               (Std. err. adjusted for 552 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |  -.0005382   .0325535    -0.02   0.987    -.0644824    .0634059
population_2001 |  -7.49e-08   9.84e-08    -0.76   0.447    -2.68e-07    1.18e-07
          _cons |   2.667413   .0692356    38.53   0.000     2.531415    2.803411
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est8 stored)

efficacy_self -- self efficacy (1-4)
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   1     |        525      20.98      21.45      21.45
        2     |        716      28.62      29.26      50.72
        3     |        579      23.14      23.66      74.38
        4     |        627      25.06      25.62     100.00
        Total |       2447      97.80     100.00           
Missing .     |         55       2.20                      
Total         |       2502     100.00                      
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      2,290
Absorbing 1 HDFE group                            F(   2,    561) =       1.40
Statistics robust to heteroskedasticity           Prob > F        =     0.2464
                                                  R-squared       =     0.0261
                                                  Adj R-squared   =     0.0140
                                                  Within R-sq.    =     0.0011
Number of clusters (comune_id) =        562       Root MSE        =     1.1068

                               (Std. err. adjusted for 562 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |  -.0139495   .0270481    -0.52   0.606    -.0670776    .0391785
population_2001 |   8.12e-08   7.69e-08     1.06   0.291    -6.98e-08    2.32e-07
          _cons |   2.576373   .0592818    43.46   0.000     2.459932    2.692815
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est9 stored)

efficacy_rep -- candidates lose touch (1-4)
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   1     |        105       4.20       4.29       4.29
        2     |        278      11.11      11.35      15.63
        3     |        790      31.57      32.24      47.88
        4     |       1277      51.04      52.12     100.00
        Total |       2450      97.92     100.00           
Missing .     |         52       2.08                      
Total         |       2502     100.00                      
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      2,293
Absorbing 1 HDFE group                            F(   2,    561) =       0.07
Statistics robust to heteroskedasticity           Prob > F        =     0.9321
                                                  R-squared       =     0.0347
                                                  Adj R-squared   =     0.0228
                                                  Within R-sq.    =     0.0000
Number of clusters (comune_id) =        562       Root MSE        =     0.8650

                               (Std. err. adjusted for 562 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |  -.0028965   .0184962    -0.16   0.876    -.0392269    .0334338
population_2001 |   1.06e-08   4.81e-08     0.22   0.826    -8.40e-08    1.05e-07
          _cons |   3.318356   .0370849    89.48   0.000     3.245513    3.391198
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est10 stored)

efficacy_cand -- candidates not parties relevant (1-4)
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   1     |        613      24.50      25.16      25.16
        2     |        545      21.78      22.37      47.54
        3     |        577      23.06      23.69      71.22
        4     |        701      28.02      28.78     100.00
        Total |       2436      97.36     100.00           
Missing .     |         66       2.64                      
Total         |       2502     100.00                      
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      2,281
Absorbing 1 HDFE group                            F(   2,    560) =       1.26
Statistics robust to heteroskedasticity           Prob > F        =     0.2843
                                                  R-squared       =     0.0204
                                                  Adj R-squared   =     0.0082
                                                  Within R-sq.    =     0.0014
Number of clusters (comune_id) =        561       Root MSE        =     1.1586

                               (Std. err. adjusted for 561 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |   .0373004   .0275877     1.35   0.177    -.0168876    .0914883
population_2001 |   1.04e-07   7.77e-08     1.34   0.181    -4.85e-08    2.57e-07
          _cons |   2.580728    .058023    44.48   0.000     2.466758    2.694697
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est11 stored)

dem_sat -- satisfied with demo in Italy (1-4)
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   1     |         42       1.68       1.70       1.70
        2     |        660      26.38      26.73      28.43
        3     |       1252      50.04      50.71      79.14
        4     |        515      20.58      20.86     100.00
        Total |       2469      98.68     100.00           
Missing .     |         33       1.32                      
Total         |       2502     100.00                      
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      2,311
Absorbing 1 HDFE group                            F(   2,    559) =       0.89
Statistics robust to heteroskedasticity           Prob > F        =     0.4120
                                                  R-squared       =     0.0457
                                                  Adj R-squared   =     0.0340
                                                  Within R-sq.    =     0.0010
Number of clusters (comune_id) =        560       Root MSE        =     0.7264

                               (Std. err. adjusted for 560 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |   .0199503   .0156478     1.27   0.203    -.0107855    .0506861
population_2001 |   1.24e-08   5.54e-08     0.22   0.823    -9.64e-08    1.21e-07
          _cons |     2.9717   .0371014    80.10   0.000     2.898825    3.044575
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est12 stored)

democrat -- supports democracy (0,1)
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   0     |        468      18.71      18.71      18.71
        1     |       2034      81.29      81.29     100.00
        Total |       2502     100.00     100.00           
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      2,344
Absorbing 1 HDFE group                            F(   2,    562) =       0.89
Statistics robust to heteroskedasticity           Prob > F        =     0.4132
                                                  R-squared       =     0.0292
                                                  Adj R-squared   =     0.0175
                                                  Within R-sq.    =     0.0008
Number of clusters (comune_id) =        563       Root MSE        =     0.4211

                               (Std. err. adjusted for 563 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |   .0020167   .0104259     0.19   0.847    -.0184618    .0224953
population_2001 |   3.95e-08   3.09e-08     1.28   0.202    -2.12e-08    1.00e-07
          _cons |   .7527013   .0227908    33.03   0.000     .7079358    .7974668
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est13 stored)

econ_worse
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   0     |       1263      50.48      51.38      51.38
        1     |       1195      47.76      48.62     100.00
        Total |       2458      98.24     100.00           
Missing .     |         44       1.76                      
Total         |       2502     100.00                      
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      2,303
Absorbing 1 HDFE group                            F(   2,    559) =       0.45
Statistics robust to heteroskedasticity           Prob > F        =     0.6351
                                                  R-squared       =     0.0368
                                                  Adj R-squared   =     0.0250
                                                  Within R-sq.    =     0.0006
Number of clusters (comune_id) =        560       Root MSE        =     0.4932

                               (Std. err. adjusted for 560 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |   .0105281   .0112078     0.94   0.348    -.0114864    .0325427
population_2001 |   2.15e-08   3.58e-08     0.60   0.548    -4.88e-08    9.19e-08
          _cons |   .5057679    .025102    20.15   0.000      .456462    .5550737
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est14 stored)

econ_worse_personal
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   0     |       1665      66.55      66.71      66.71
        1     |        831      33.21      33.29     100.00
        Total |       2496      99.76     100.00           
Missing .     |          6       0.24                      
Total         |       2502     100.00                      
-----------------------------------------------------------
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      2,338
Absorbing 1 HDFE group                            F(   2,    562) =       0.06
Statistics robust to heteroskedasticity           Prob > F        =     0.9397
                                                  R-squared       =     0.0468
                                                  Adj R-squared   =     0.0352
                                                  Within R-sq.    =     0.0001
Number of clusters (comune_id) =        563       Root MSE        =     0.4755

                               (Std. err. adjusted for 563 clusters in comune_id)
---------------------------------------------------------------------------------
                |               Robust
   independence | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
        log_ugs |   .0025733   .0102488     0.25   0.802    -.0175573    .0227038
population_2001 |  -3.67e-09   3.65e-08    -0.10   0.920    -7.55e-08    6.81e-08
          _cons |   .3713981   .0229491    16.18   0.000     .3263216    .4164747
---------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est15 stored)

.                 * coefplot:
.                 coefplot ///
>                 (est1, mlabels(log_ugs = 12 "{bf:Ulivo 1996 (0,1)}") pstyle(p9) msymbol(D)) ///
>                 (est2, mlabels(log_ugs = 12 "{bf:POL 1996 (0,1)}") pstyle(p6) msymbol(D))  ///
>                 (est3, mlabels(log_ugs = 1 "{bf:LN 1996 (0,1)}") pstyle(p4) msymbol(D)) ///
>                 (est4, mlabels(log_ugs = 11 "{bf:PD 1996 (0,1)}") pstyle(p3) msymbol(S)) ///
>                 (est5, mlabels(log_ugs = 11 "{bf:FI 1996 (0,1)}") pstyle(p1) msymbol(S))  ///
>                 (est6, mlabels(log_ugs = 11 "{bf:AN 1996 (0,1)}") pstyle(p7) msymbol(S)) ///
>                 (est7, mlabels(log_ugs = 1 "{bf:LN 1996 (0,1)}") pstyle(p4) msymbol(S)) ///
>                 (est8, mlabels(log_ugs = 1 "{bf:left-right self (1-5)}") pstyle(p5)) ///
>                 (est9, mlabels(log_ugs = 11 "{bf:self efficacy (1-4)}") pstyle(p5)) ///
>                 (est10, mlabels(log_ugs = 11 "{bf:candidates lose touch (1-4)}") pstyle(p5)) ///
>                 (est11, mlabels(log_ugs = 1 "{bf:candidates not parties relevant (1-4)}") pstyle(p5)) ///
>                 (est12, mlabels(log_ugs = 1 "{bf:satisfied with demo in Italy (1-4)}") pstyle(p5)) ///
>                 (est13, mlabels(log_ugs = 1 "{bf:supports democracy (0,1)}") pstyle(p5)) ///
>                 (est14, mlabels(log_ugs = 1 "{bf:econ Italy worse (0,1)}") pstyle(p5)) ///
>                 (est15, mlabels(log_ugs = 1 "{bf:econ self worse (0,1)}") pstyle(p5)) ///
>                 , ///
>                 keep(log_ugs) ///
>                 ciopts(lwidth(0.4 ..)) mlwidth(medthick) msize(medsmall) mfcolor(white) ///
>                 xline(0)  ///
>                 grid(none) ///
>                 legend(off) ///
>                 ylabel("") ///
>                 xtitle("OLS coefficients of {bf:UGS distance} on ...")

.                 * save as pdf: 
.                 graph export "$figures/figa8_independence.pdf", replace
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/figa8_independence.pdf saved as PDF format

. 
.                 * IV placebos (tab a5)
.                 use "$data_coded/placebased_independence.dta", clear
(Written by R)

.                 cls 

.                 eststo clear

.                 foreach var of varlist vote96maj_1 vote96maj_2 vote96maj_3 vote96pro_3 vote96pro_5 vote96pro_7 vote96pro_8 lr effi
> cacy_* dem_sat democrat econ_worse econ_worse_personal {
  2.                         *reghdfe `var' log_ugs population_2001, absorb(constant) cluster(comune_id)
.                         *reghdfe `var' log_ugs population_2001, absorb(province_id) cluster(comune_id)
.                         eststo: ivreghdfe `var' (std_wn_treat_campaign = c.log_hist##c.log_ugs) population_2001 [pweight=weight], 
> absorb(province_id) cluster(comune_id)
  3.                 }
(sum of wgt is     1.7573e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    533               Number of obs =     1844
                                                      F(  2,   532) =     1.15
                                                      Prob > F      =   0.3183
Total (centered) SS     =  432.4236533                Centered R2   =  -0.0004
Total (uncentered) SS   =  432.4236533                Uncentered R2 =  -0.0004
Residual SS             =   432.600356                Root MSE      =    .4882

---------------------------------------------------------------------------------------
                      |               Robust
          vote96maj_1 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.0118936   .0090537    -1.31   0.190     -.029679    .0058918
      population_2001 |   5.73e-08   3.95e-08     1.45   0.147    -2.02e-08    1.35e-07
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            147.649
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             1751.301
                         (Kleibergen-Paap rk Wald F statistic):        207.556
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.547
                                                   Chi-sq(2) P-val =    0.7606
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est1 stored)
(sum of wgt is     1.7573e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    533               Number of obs =     1844
                                                      F(  2,   532) =     1.19
                                                      Prob > F      =   0.3037
Total (centered) SS     =  410.7981117                Centered R2   =   0.0013
Total (uncentered) SS   =  410.7981117                Uncentered R2 =   0.0013
Residual SS             =  410.2647847                Root MSE      =    .4754

---------------------------------------------------------------------------------------
                      |               Robust
          vote96maj_2 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .0131003   .0084928     1.54   0.124    -.0035832    .0297837
      population_2001 |  -3.97e-08   3.97e-08    -1.00   0.318    -1.18e-07    3.83e-08
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            147.649
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             1751.301
                         (Kleibergen-Paap rk Wald F statistic):        207.556
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         1.771
                                                   Chi-sq(2) P-val =    0.4124
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est2 stored)
(sum of wgt is     1.7573e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    533               Number of obs =     1844
                                                      F(  2,   532) =     2.70
                                                      Prob > F      =   0.0679
Total (centered) SS     =  95.28625801                Centered R2   =   0.0057
Total (uncentered) SS   =  95.28625801                Uncentered R2 =   0.0057
Residual SS             =    94.740909                Root MSE      =    .2285

---------------------------------------------------------------------------------------
                      |               Robust
          vote96maj_3 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.0046823   .0041663    -1.12   0.262    -.0128667    .0035021
      population_2001 |  -2.33e-08   2.01e-08    -1.16   0.248    -6.29e-08    1.63e-08
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            147.649
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             1751.301
                         (Kleibergen-Paap rk Wald F statistic):        207.556
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.494
                                                   Chi-sq(2) P-val =    0.7812
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est3 stored)
(sum of wgt is     1.8913e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    534               Number of obs =     1933
                                                      F(  2,   533) =     0.07
                                                      Prob > F      =   0.9282
Total (centered) SS     =  372.1611584                Centered R2   =   0.0001
Total (uncentered) SS   =  372.1611584                Uncentered R2 =   0.0001
Residual SS             =  372.1191906                Root MSE      =    .4421

---------------------------------------------------------------------------------------
                      |               Robust
          vote96pro_3 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .0010604   .0086304     0.12   0.902    -.0158933    .0180141
      population_2001 |   6.23e-09   3.71e-08     0.17   0.867    -6.66e-08    7.90e-08
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            144.139
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             1815.711
                         (Kleibergen-Paap rk Wald F statistic):        203.486
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.655
                                                   Chi-sq(2) P-val =    0.7209
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est4 stored)
(sum of wgt is     1.8913e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    534               Number of obs =     1933
                                                      F(  2,   533) =     1.91
                                                      Prob > F      =   0.1497
Total (centered) SS     =  276.5547459                Centered R2   =   0.0002
Total (uncentered) SS   =  276.5547459                Uncentered R2 =   0.0002
Residual SS             =  276.4941495                Root MSE      =    .3811

---------------------------------------------------------------------------------------
                      |               Robust
          vote96pro_5 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .0123075   .0063122     1.95   0.052    -.0000923    .0247073
      population_2001 |  -3.63e-08   3.01e-08    -1.20   0.229    -9.54e-08    2.29e-08
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            144.139
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             1815.711
                         (Kleibergen-Paap rk Wald F statistic):        203.486
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.364
                                                   Chi-sq(2) P-val =    0.8335
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est5 stored)
(sum of wgt is     1.8913e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    534               Number of obs =     1933
                                                      F(  2,   533) =     0.02
                                                      Prob > F      =   0.9830
Total (centered) SS     =  227.6001549                Centered R2   =  -0.0001
Total (uncentered) SS   =  227.6001549                Uncentered R2 =  -0.0001
Residual SS             =  227.6257458                Root MSE      =    .3458

---------------------------------------------------------------------------------------
                      |               Robust
          vote96pro_7 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.0010185   .0057157    -0.18   0.859    -.0122465    .0102095
      population_2001 |   2.75e-09   3.70e-08     0.07   0.941    -6.99e-08    7.54e-08
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            144.139
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             1815.711
                         (Kleibergen-Paap rk Wald F statistic):        203.486
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         3.884
                                                   Chi-sq(2) P-val =    0.1434
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est6 stored)
(sum of wgt is     1.8913e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    534               Number of obs =     1933
                                                      F(  2,   533) =     1.96
                                                      Prob > F      =   0.1416
Total (centered) SS     =  132.7198816                Centered R2   =   0.0028
Total (uncentered) SS   =  132.7198816                Uncentered R2 =   0.0028
Residual SS             =  132.3466624                Root MSE      =    .2636

---------------------------------------------------------------------------------------
                      |               Robust
          vote96pro_8 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.0016806   .0050493    -0.33   0.739    -.0115995    .0082384
      population_2001 |  -3.37e-08   2.39e-08    -1.41   0.160    -8.07e-08    1.33e-08
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            144.139
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             1815.711
                         (Kleibergen-Paap rk Wald F statistic):        203.486
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         1.187
                                                   Chi-sq(2) P-val =    0.5525
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est7 stored)
(sum of wgt is     2.0753e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    552               Number of obs =     2134
                                                      F(  2,   551) =     0.36
                                                      Prob > F      =   0.6989
Total (centered) SS     =   3826.18277                Centered R2   =   0.0002
Total (uncentered) SS   =   3826.18277                Uncentered R2 =   0.0002
Residual SS             =  3825.291839                Root MSE      =    1.348

---------------------------------------------------------------------------------------
                      |               Robust
                   lr | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .0012064   .0231493     0.05   0.958    -.0442652    .0466781
      population_2001 |  -7.83e-08   1.15e-07    -0.68   0.495    -3.04e-07    1.47e-07
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            151.849
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             2018.282
                         (Kleibergen-Paap rk Wald F statistic):        224.785
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.321
                                                   Chi-sq(2) P-val =    0.8517
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est8 stored)
(sum of wgt is     2.2663e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    562               Number of obs =     2290
                                                      F(  2,   561) =     1.62
                                                      Prob > F      =   0.1992
Total (centered) SS     =  2772.500503                Centered R2   =   0.0017
Total (uncentered) SS   =  2772.500503                Uncentered R2 =   0.0017
Residual SS             =  2767.723934                Root MSE      =    1.106

---------------------------------------------------------------------------------------
                      |               Robust
        efficacy_self | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.0128545   .0188686    -0.68   0.496    -.0499163    .0242073
      population_2001 |   1.51e-07   9.04e-08     1.67   0.095    -2.64e-08    3.29e-07
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            154.402
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             2029.395
                         (Kleibergen-Paap rk Wald F statistic):        203.060
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         4.818
                                                   Chi-sq(2) P-val =    0.0899
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est9 stored)
(sum of wgt is     2.2752e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    562               Number of obs =     2293
                                                      F(  2,   561) =     0.23
                                                      Prob > F      =   0.7942
Total (centered) SS     =  1694.147971                Centered R2   =   0.0002
Total (uncentered) SS   =  1694.147971                Uncentered R2 =   0.0002
Residual SS             =  1693.801768                Root MSE      =     .865

---------------------------------------------------------------------------------------
                      |               Robust
         efficacy_rep | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.0071742   .0139841    -0.51   0.608    -.0346418    .0202933
      population_2001 |   4.10e-08   6.06e-08     0.68   0.499    -7.80e-08    1.60e-07
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            155.519
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             2041.746
                         (Kleibergen-Paap rk Wald F statistic):        199.616
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.439
                                                   Chi-sq(2) P-val =    0.8029
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est10 stored)
(sum of wgt is     2.2588e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    561               Number of obs =     2281
                                                      F(  2,   560) =     1.74
                                                      Prob > F      =   0.1770
Total (centered) SS     =  3027.263017                Centered R2   =   0.0022
Total (uncentered) SS   =  3027.263017                Uncentered R2 =   0.0022
Residual SS             =  3020.744395                Root MSE      =    1.158

---------------------------------------------------------------------------------------
                      |               Robust
        efficacy_cand | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.0319241   .0193752    -1.65   0.100    -.0699811    .0061329
      population_2001 |   1.56e-07   9.04e-08     1.73   0.084    -2.11e-08    3.34e-07
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            157.825
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             2011.103
                         (Kleibergen-Paap rk Wald F statistic):        206.874
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         3.583
                                                   Chi-sq(2) P-val =    0.1667
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est11 stored)
(sum of wgt is     2.3022e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    560               Number of obs =     2311
                                                      F(  2,   559) =     0.28
                                                      Prob > F      =   0.7556
Total (centered) SS     =  1205.434433                Centered R2   =   0.0005
Total (uncentered) SS   =  1205.434433                Uncentered R2 =   0.0005
Residual SS             =  1204.809775                Root MSE      =    .7266

---------------------------------------------------------------------------------------
                      |               Robust
              dem_sat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.0067379   .0112258    -0.60   0.549    -.0287879    .0153121
      population_2001 |   3.42e-09   6.58e-08     0.05   0.959    -1.26e-07    1.33e-07
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            154.856
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             2072.906
                         (Kleibergen-Paap rk Wald F statistic):        205.882
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         1.474
                                                   Chi-sq(2) P-val =    0.4786
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est12 stored)
(sum of wgt is     2.3444e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    563               Number of obs =     2344
                                                      F(  2,   562) =     0.79
                                                      Prob > F      =   0.4525
Total (centered) SS     =  410.7605285                Centered R2   =   0.0007
Total (uncentered) SS   =  410.7605285                Uncentered R2 =   0.0007
Residual SS             =  410.4779356                Root MSE      =    .4211

---------------------------------------------------------------------------------------
                      |               Robust
             democrat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .0016083   .0072866     0.22   0.825     -.012704    .0159206
      population_2001 |   3.03e-08   3.37e-08     0.90   0.369    -3.59e-08    9.65e-08
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            156.792
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             2107.361
                         (Kleibergen-Paap rk Wald F statistic):        207.243
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.189
                                                   Chi-sq(2) P-val =    0.9099
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est13 stored)
(sum of wgt is     2.2886e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    560               Number of obs =     2303
                                                      F(  2,   559) =     0.50
                                                      Prob > F      =   0.6054
Total (centered) SS     =  553.4023944                Centered R2   =   0.0007
Total (uncentered) SS   =  553.4023944                Uncentered R2 =   0.0007
Residual SS             =  553.0277709                Root MSE      =    .4931

---------------------------------------------------------------------------------------
                      |               Robust
           econ_worse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.0076472   .0078319    -0.98   0.329    -.0230306    .0077363
      population_2001 |   3.16e-08   3.92e-08     0.81   0.420    -4.54e-08    1.09e-07
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            158.052
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             2089.009
                         (Kleibergen-Paap rk Wald F statistic):        220.297
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         1.928
                                                   Chi-sq(2) P-val =    0.3814
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est14 stored)
(sum of wgt is     2.3353e+03)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on comune_id

Number of clusters (comune_id) =    563               Number of obs =     2338
                                                      F(  2,   562) =     0.04
                                                      Prob > F      =   0.9637
Total (centered) SS     =  522.0521352                Centered R2   =  -0.0001
Total (uncentered) SS   =  522.0521352                Uncentered R2 =  -0.0001
Residual SS             =  522.0979222                Root MSE      =    .4755

---------------------------------------------------------------------------------------
                      |               Robust
  econ_worse_personal | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .0008274   .0075806     0.11   0.913    -.0140623    .0157172
      population_2001 |  -1.10e-08   4.18e-08    -0.26   0.793    -9.31e-08    7.12e-08
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            156.884
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             2094.466
                         (Kleibergen-Paap rk Wald F statistic):        205.448
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.353
                                                   Chi-sq(2) P-val =    0.8382
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        27           0          27     |
-----------------------------------------------------+
(est15 stored)

.                 * create a LaTeX Table:
.                 estfe est*, labels(province_id "Province FE")

.                 * save table:
.                 esttab est* using "$tables/taba5_placebos.tex", replace  ///
>                 indicate( `r(indicate_fe)' , labels(\checkmark)) ///
>                 se nobaselevels nostar label se(3) b(3) ///
>                 stats(N r2_a r2_a_within rmse idstat, labels("\$ Obs$" "\$ adj.R^2$" "\$ adj.R^2 (within)$" "\$ RMSE$" "Kleibergen
> -Paap" "Cragg-Donald Wald F statistic")) ///
>                 note("\emph{Note:} clustered standard errors by province") ///
>                 substitute(_ _) 
(output written to /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/tables/taba5_placebos.tex)

. 
.                 * IV estimates (tab a6)
.                 use "$data_coded/placebased_regional.dta", clear 

.                 **instrument 3: internet*early days
.                 eststo clear

.                 *eststo: ivreghdfe referendum_no (std_wn_treat_campaign = c.hist_days##c.km_to_ugs), absorb(province_id) cluster(p
> rovince_id)  first
.                 eststo: reghdfe referendum_no std_wn_treat_campaign `controls', absorb(province_id)  cluster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  10,    109) =     126.38
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7127
                                                  Adj R-squared   =     0.7082
                                                  Within R-sq.    =     0.3451
Number of clusters (province_id) =        110     Root MSE        =     4.6887

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2060627   .0760245     2.71   0.008     .0553847    .3567407
             m5s_c_13 |   .2465947   .0512954     4.81   0.000     .1449289    .3482604
              pd_c_13 |  -.5133675   .0334788   -15.33   0.000    -.5797213   -.4470136
           turnout_13 |   .0034561    .035689     0.10   0.923    -.0672784    .0741906
               income |  -.0004788   .0000941    -5.09   0.000    -.0006652   -.0002923
         unemployment |   .1778951   .0270978     6.56   0.000     .1241881    .2316021
           university |    -.25782   .0575571    -4.48   0.000    -.3718964   -.1437437
               no_edu |  -.1826568   .0227176    -8.04   0.000    -.2276823   -.1376313
           foreigners |  -.0238165   .0364951    -0.65   0.515    -.0961486    .0485155
       pop_density_16 |   .0002173   .0001023     2.12   0.036     .0000145    .0004201
                _cons |   76.25067   2.056471    37.08   0.000     72.17482    80.32653
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est1 stored)

.                                 reghdfe std_wn_treat_campaign c.hist_days##c.km_to_ugs population_2001, absorb(province_id) cluste
> r(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,820
Absorbing 1 HDFE group                            F(   4,    106) =     108.49
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5358
                                                  Adj R-squared   =     0.5292
                                                  Within R-sq.    =     0.4766
Number of clusters (province_id) =        107     Root MSE        =     0.4693

                                     (Std. err. adjusted for 107 clusters in province_id)
-----------------------------------------------------------------------------------------
                        |               Robust
  std_wn_treat_campaign | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
------------------------+----------------------------------------------------------------
              hist_days |   .0007708   .0000431    17.87   0.000     .0006853    .0008563
              km_to_ugs |  -.0047264   .0009374    -5.04   0.000    -.0065849    -.002868
                        |
c.hist_days#c.km_to_ugs |   .0000235   5.36e-06     4.38   0.000     .0000128    .0000341
                        |
        population_2001 |  -1.05e-06   3.57e-07    -2.93   0.004    -1.76e-06   -3.38e-07
                  _cons |   .1283294   .0136387     9.41   0.000     .1012894    .1553694
-----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       107         107           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

.                 eststo: ivreghdfe referendum_no (std_wn_treat_campaign = c.hist_days##c.km_to_ugs) population_2001, absorb(provinc
> e_id) cluster(province_id) first
(MWFE estimator converged in 1 iterations)

Unable to store first-stage regression of std_wn_treat_campaign.


First-stage regressions
-----------------------

Unable to display all first-stage regressions.
There may be insufficient room to store results using -estimates store-,
or names of endogenous regressors may be too long to store the results.
Try dropping one or more estimation results using -estimates drop-,
using the -savefprefix- option, or using shorter variable names.



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,   106)  P-val | SW Chi-sq(  3) P-val | SW F(  3,   106)
std_wn_treat |     144.41    0.0000 |      437.53   0.0000 |      144.41

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID F test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV relative bias     9.08
                                   20% maximal IV relative bias     6.46
                                   30% maximal IV relative bias     5.39
                                   10% maximal IV size             22.30
                                   15% maximal IV size             12.83
                                   20% maximal IV size              9.54
                                   25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for i.i.d. errors only.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(3)=42.97    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                    2232.24
Kleibergen-Paap Wald rk F statistic                               144.41

Stock-Yogo weak ID test critical values for K1=1 and L1=3:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV relative bias     9.08
                                   20% maximal IV relative bias     6.46
                                   30% maximal IV relative bias     5.39
                                   10% maximal IV size             22.30
                                   15% maximal IV size             12.83
                                   20% maximal IV size              9.54
                                   25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,106)=       2.24     P-val=0.0873
Anderson-Rubin Wald test           Chi-sq(3)=      6.80     P-val=0.0785
Stock-Wright LM S statistic        Chi-sq(3)=      8.31     P-val=0.0401

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =        107
Number of observations               N  =       7820
Number of regressors                 K  =          2
Number of endogenous regressors      K1 =          1
Number of instruments                L  =          4
Number of excluded instruments       L1 =          3

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on province_id

Number of clusters (province_id) =    107             Number of obs =     7820
                                                      F(  2,   106) =     7.78
                                                      Prob > F      =   0.0007
Total (centered) SS     =  268711.3998                Centered R2   =   0.0016
Total (uncentered) SS   =  268711.3998                Uncentered R2 =   0.0016
Residual SS             =  268271.5936                Root MSE      =    5.858

---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .4508873   .1877293     2.40   0.018     .0786956     .823079
      population_2001 |  -2.19e-06   9.63e-07    -2.27   0.025    -4.09e-06   -2.77e-07
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             42.974
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             2232.245
                         (Kleibergen-Paap rk Wald F statistic):        144.407
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         4.198
                                                   Chi-sq(2) P-val =    0.1226
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: hist_days km_to_ugs c.hist_days#c.km_to_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       107         107           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est2 stored)

.                 eststo: ivreghdfe referendum_no (std_wn_treat_campaign = c.log_hist##c.log_ugs) population_2001, absorb(province_i
> d) cluster(province_id) first
(MWFE estimator converged in 1 iterations)

Unable to store first-stage regression of std_wn_treat_campaign.


First-stage regressions
-----------------------

Unable to display all first-stage regressions.
There may be insufficient room to store results using -estimates store-,
or names of endogenous regressors may be too long to store the results.
Try dropping one or more estimation results using -estimates drop-,
using the -savefprefix- option, or using shorter variable names.



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,   106)  P-val | SW Chi-sq(  3) P-val | SW F(  3,   106)
std_wn_treat |     281.67    0.0000 |      853.43   0.0000 |      281.67

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID F test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV relative bias     9.08
                                   20% maximal IV relative bias     6.46
                                   30% maximal IV relative bias     5.39
                                   10% maximal IV size             22.30
                                   15% maximal IV size             12.83
                                   20% maximal IV size              9.54
                                   25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for i.i.d. errors only.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(3)=43.04    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                    5029.40
Kleibergen-Paap Wald rk F statistic                               281.67

Stock-Yogo weak ID test critical values for K1=1 and L1=3:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV relative bias     9.08
                                   20% maximal IV relative bias     6.46
                                   30% maximal IV relative bias     5.39
                                   10% maximal IV size             22.30
                                   15% maximal IV size             12.83
                                   20% maximal IV size              9.54
                                   25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,106)=       2.56     P-val=0.0586
Anderson-Rubin Wald test           Chi-sq(3)=      7.77     P-val=0.0511
Stock-Wright LM S statistic        Chi-sq(3)=      8.96     P-val=0.0298

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =        107
Number of observations               N  =       7820
Number of regressors                 K  =          2
Number of endogenous regressors      K1 =          1
Number of instruments                L  =          4
Number of excluded instruments       L1 =          3

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on province_id

Number of clusters (province_id) =    107             Number of obs =     7820
                                                      F(  2,   106) =    10.11
                                                      Prob > F      =   0.0001
Total (centered) SS     =  268711.3998                Centered R2   =   0.0016
Total (uncentered) SS   =  268711.3998                Uncentered R2 =   0.0016
Residual SS             =  268271.5691                Root MSE      =    5.858

---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .4508353   .1651556     2.73   0.007     .1233982    .7782724
      population_2001 |  -2.19e-06   9.72e-07    -2.25   0.027    -4.11e-06   -2.59e-07
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             43.044
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             5029.396
                         (Kleibergen-Paap rk Wald F statistic):        281.674
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         3.044
                                                   Chi-sq(2) P-val =    0.2183
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       107         107           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est3 stored)

.                 eststo: ivreghdfe referendum_no (std_wn_treat_campaign = c.log_hist##c.log_ugs) `controls', absorb(province_id) cl
> uster(province_id) first
(MWFE estimator converged in 1 iterations)

Unable to store first-stage regression of std_wn_treat_campaign.


First-stage regressions
-----------------------

Unable to display all first-stage regressions.
There may be insufficient room to store results using -estimates store-,
or names of endogenous regressors may be too long to store the results.
Try dropping one or more estimation results using -estimates drop-,
using the -savefprefix- option, or using shorter variable names.



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,   109)  P-val | SW Chi-sq(  3) P-val | SW F(  3,   109)
std_wn_treat |     286.85    0.0000 |      869.77   0.0000 |      286.85

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID F test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV relative bias     9.08
                                   20% maximal IV relative bias     6.46
                                   30% maximal IV relative bias     5.39
                                   10% maximal IV size             22.30
                                   15% maximal IV size             12.83
                                   20% maximal IV size              9.54
                                   25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for i.i.d. errors only.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(3)=52.47    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                    4461.38
Kleibergen-Paap Wald rk F statistic                               286.85

Stock-Yogo weak ID test critical values for K1=1 and L1=3:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV relative bias     9.08
                                   20% maximal IV relative bias     6.46
                                   30% maximal IV relative bias     5.39
                                   10% maximal IV size             22.30
                                   15% maximal IV size             12.83
                                   20% maximal IV size              9.54
                                   25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,109)=       8.90     P-val=0.0000
Anderson-Rubin Wald test           Chi-sq(3)=     26.97     P-val=0.0000
Stock-Wright LM S statistic        Chi-sq(3)=     25.16     P-val=0.0000

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =        110
Number of observations               N  =       7803
Number of regressors                 K  =         10
Number of endogenous regressors      K1 =          1
Number of instruments                L  =         12
Number of excluded instruments       L1 =          3

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on province_id

Number of clusters (province_id) =    110             Number of obs =     7803
                                                      F( 10,   109) =   126.32
                                                      Prob > F      =   0.0000
Total (centered) SS     =    257936.02                Centered R2   =   0.3450
Total (uncentered) SS   =    257936.02                Uncentered R2 =   0.3450
Residual SS             =  168936.4796                Root MSE      =    4.656

---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2867601   .0925996     3.10   0.002     .1032307    .4702896
             m5s_c_13 |   .2462237   .0511835     4.81   0.000     .1447796    .3476677
              pd_c_13 |  -.5130745   .0334944   -15.32   0.000    -.5794593   -.4466898
           turnout_13 |   .0040653   .0355746     0.11   0.909    -.0664424    .0745731
               income |  -.0004781    .000094    -5.08   0.000    -.0006645   -.0002917
         unemployment |   .1775249   .0270846     6.55   0.000     .1238442    .2312056
           university |  -.2622673   .0570002    -4.60   0.000    -.3752398   -.1492948
               no_edu |  -.1821523   .0227384    -8.01   0.000     -.227219   -.1370855
           foreigners |    -.02445   .0364005    -0.67   0.503    -.0965947    .0476947
       pop_density_16 |   .0002039   .0001044     1.95   0.053    -3.03e-06    .0004108
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             52.470
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             4461.380
                         (Kleibergen-Paap rk Wald F statistic):        286.846
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    13.91
                                         10% maximal IV relative bias     9.08
                                         20% maximal IV relative bias     6.46
                                         30% maximal IV relative bias     5.39
                                         10% maximal IV size             22.30
                                         15% maximal IV size             12.83
                                         20% maximal IV size              9.54
                                         25% maximal IV size              7.80
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):        12.756
                                                   Chi-sq(2) P-val =    0.0017
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: m5s_c_13 pd_c_13 turnout_13 income unemployment
                      university no_edu foreigners pop_density_16
Excluded instruments: log_hist log_ugs c.log_hist#c.log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est4 stored)

.                 **only ugs distance:
.                 *eststo: ivreghdfe referendum_no (std_wn_treat_campaign = km_to_ugs), absorb(province_id) cluster(province_id)  fi
> rst
.                 eststo: ivreghdfe referendum_no (std_wn_treat_campaign = km_to_ugs) population_2001, absorb(province_id) cluster(p
> rovince_id)  first
(MWFE estimator converged in 1 iterations)

Unable to store first-stage regression of std_wn_treat_campaign.


First-stage regressions
-----------------------

Unable to display all first-stage regressions.
There may be insufficient room to store results using -estimates store-,
or names of endogenous regressors may be too long to store the results.
Try dropping one or more estimation results using -estimates drop-,
using the -savefprefix- option, or using shorter variable names.



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  1,   106)  P-val | SW Chi-sq(  1) P-val | SW F(  1,   106)
std_wn_treat |      26.40    0.0000 |       26.65   0.0000 |       26.40

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID F test critical values for single endogenous regressor:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for i.i.d. errors only.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=25.49    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     152.36
Kleibergen-Paap Wald rk F statistic                                26.40

Stock-Yogo weak ID test critical values for K1=1 and L1=1:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(1,106)=       3.71     P-val=0.0568
Anderson-Rubin Wald test           Chi-sq(1)=      3.74     P-val=0.0530
Stock-Wright LM S statistic        Chi-sq(1)=      5.19     P-val=0.0227

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =        107
Number of observations               N  =       7820
Number of regressors                 K  =          2
Number of endogenous regressors      K1 =          1
Number of instruments                L  =          2
Number of excluded instruments       L1 =          1

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on province_id

Number of clusters (province_id) =    107             Number of obs =     7820
                                                      F(  2,   106) =     2.14
                                                      Prob > F      =   0.1232
Total (centered) SS     =  268711.3998                Centered R2   =  -0.1819
Total (uncentered) SS   =  268711.3998                Uncentered R2 =  -0.1819
Residual SS             =  317578.7663                Root MSE      =    6.374

---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   4.331309   2.096543     2.07   0.041     .1747075     8.48791
      population_2001 |  -.0000128   7.64e-06    -1.68   0.097     -.000028    2.34e-06
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             25.487
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              152.355
                         (Kleibergen-Paap rk Wald F statistic):         26.396
Stock-Yogo weak ID test critical values: 10% maximal IV size             16.38
                                         15% maximal IV size              8.96
                                         20% maximal IV size              6.66
                                         25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: km_to_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       107         107           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est5 stored)

.                 eststo: ivreghdfe referendum_no (std_wn_treat_campaign = log_ugs) population_2001, absorb(province_id) cluster(pro
> vince_id)  first
(MWFE estimator converged in 1 iterations)

Unable to store first-stage regression of std_wn_treat_campaign.


First-stage regressions
-----------------------

Unable to display all first-stage regressions.
There may be insufficient room to store results using -estimates store-,
or names of endogenous regressors may be too long to store the results.
Try dropping one or more estimation results using -estimates drop-,
using the -savefprefix- option, or using shorter variable names.



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  1,   106)  P-val | SW Chi-sq(  1) P-val | SW F(  1,   106)
std_wn_treat |      76.17    0.0000 |       76.91   0.0000 |       76.17

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID F test critical values for single endogenous regressor:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for i.i.d. errors only.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=35.43    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     491.49
Kleibergen-Paap Wald rk F statistic                                76.17

Stock-Yogo weak ID test critical values for K1=1 and L1=1:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(1,106)=       3.83     P-val=0.0528
Anderson-Rubin Wald test           Chi-sq(1)=      3.87     P-val=0.0491
Stock-Wright LM S statistic        Chi-sq(1)=      5.52     P-val=0.0188

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =        107
Number of observations               N  =       7820
Number of regressors                 K  =          2
Number of endogenous regressors      K1 =          1
Number of instruments                L  =          2
Number of excluded instruments       L1 =          1

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on province_id

Number of clusters (province_id) =    107             Number of obs =     7820
                                                      F(  2,   106) =     2.48
                                                      Prob > F      =   0.0885
Total (centered) SS     =  268711.3998                Centered R2   =  -0.0339
Total (uncentered) SS   =  268711.3998                Uncentered R2 =  -0.0339
Residual SS             =  277812.1644                Root MSE      =    5.962

---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   2.117279   1.032738     2.05   0.043     .0697762    4.164782
      population_2001 |  -6.75e-06   3.23e-06    -2.09   0.039    -.0000131   -3.47e-07
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             35.434
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              491.493
                         (Kleibergen-Paap rk Wald F statistic):         76.175
Stock-Yogo weak ID test critical values: 10% maximal IV size             16.38
                                         15% maximal IV size              8.96
                                         20% maximal IV size              6.66
                                         25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: population_2001
Excluded instruments: log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       107         107           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est6 stored)

.                 eststo: ivreghdfe referendum_no (std_wn_treat_campaign = log_ugs) `controls', absorb(province_id) cluster(province
> _id)  first
(MWFE estimator converged in 1 iterations)

Unable to store first-stage regression of std_wn_treat_campaign.


First-stage regressions
-----------------------

Unable to display all first-stage regressions.
There may be insufficient room to store results using -estimates store-,
or names of endogenous regressors may be too long to store the results.
Try dropping one or more estimation results using -estimates drop-,
using the -savefprefix- option, or using shorter variable names.



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  1,   109)  P-val | SW Chi-sq(  1) P-val | SW F(  1,   109)
std_wn_treat |      64.38    0.0000 |       65.06   0.0000 |       64.38

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID F test critical values for single endogenous regressor:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for i.i.d. errors only.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=36.23    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     192.41
Kleibergen-Paap Wald rk F statistic                                64.38

Stock-Yogo weak ID test critical values for K1=1 and L1=1:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(1,109)=      11.31     P-val=0.0011
Anderson-Rubin Wald test           Chi-sq(1)=     11.43     P-val=0.0007
Stock-Wright LM S statistic        Chi-sq(1)=     12.40     P-val=0.0004

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =        110
Number of observations               N  =       7803
Number of regressors                 K  =         10
Number of endogenous regressors      K1 =          1
Number of instruments                L  =         10
Number of excluded instruments       L1 =          1

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on province_id

Number of clusters (province_id) =    110             Number of obs =     7803
                                                      F( 10,   109) =   133.53
                                                      Prob > F      =   0.0000
Total (centered) SS     =    257936.02                Centered R2   =   0.2919
Total (uncentered) SS   =    257936.02                Uncentered R2 =   0.2919
Residual SS             =  182639.8492                Root MSE      =    4.841

---------------------------------------------------------------------------------------
                      |               Robust
        referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   2.342993   .7527651     3.11   0.002     .8510366    3.834948
             m5s_c_13 |   .2335569   .0514906     4.54   0.000     .1315042    .3356096
              pd_c_13 |  -.5069184   .0342936   -14.78   0.000    -.5748872   -.4389496
           turnout_13 |   .0221651   .0365598     0.61   0.546    -.0502951    .0946254
               income |  -.0004636   .0000951    -4.87   0.000    -.0006521    -.000275
         unemployment |   .1675621   .0287861     5.82   0.000      .110509    .2246152
           university |  -.3731377   .0741885    -5.03   0.000     -.520177   -.2260985
               no_edu |  -.1695365   .0213469    -7.94   0.000    -.2118453   -.1272277
           foreigners |  -.0418068   .0385342    -1.08   0.280    -.1181803    .0345666
       pop_density_16 |  -.0001565   .0002053    -0.76   0.447    -.0005635    .0002504
---------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             36.232
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              192.409
                         (Kleibergen-Paap rk Wald F statistic):         64.385
Stock-Yogo weak ID test critical values: 10% maximal IV size             16.38
                                         15% maximal IV size              8.96
                                         20% maximal IV size              6.66
                                         25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         std_wn_treat_campaign
Included instruments: m5s_c_13 pd_c_13 turnout_13 income unemployment
                      university no_edu foreigners pop_density_16
Excluded instruments: log_ugs
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est7 stored)

.                 ***create a LaTeX Table:
.                 estfe est*, labels(province_id "Province FE")

.                 
.                 esttab est* using "$tables/taba6_instrument.tex", replace  ///
>                 indicate( `r(indicate_fe)' "Population 2001=population_2001" "Post controls=m5s_c_13", labels(\checkmark)) ///
>                 se nobaselevels nostar label se(2) b(2) ///
>                 drop(pd_c_13 turnout_13 income unemployment university no_edu foreigners pop_density_16) ///
>                 stats(N N_clust rmse widstat, labels("Obs" "Provinces" "RMSE" "Kleibergen-Paap" "Cragg-Donald Wald F statistic")) 
> ///
>                 mtitles("OLS" "IV: Hist $\times$ UGS" "IV: log(Hist $\times$ UGS)" "IV: log(Hist $\times$ UGS)" "IV: UGS" "IV: log
> (UGS)" "IV: log(UGS)") ///
>                 note("\emph{Note:} Clustered standard errors by province in parentheses. Controls omitted from table: M5S: \% vote
> s 2013, PD: \% votes 2013, \% turnout 2013, income per cap, \% unemployed, \% university degree, \% low education, \% foreigners, 
> population density.") ///
>                 substitute(_ _) 
(output written to /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/tables/taba6_instrument.tex)

. 
. 
.         // adjacent municipalities (tab a8)
.         cls

.         eststo clear

.         eststo: reghdfe referendum_no std_wn_neigh_treat_campaign if std_wn_treat_campaign==0, absorb(province_id) cluster(provinc
> e_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,373
Absorbing 1 HDFE group                            F(   1,    109) =       4.03
Statistics robust to heteroskedasticity           Prob > F        =     0.0472
                                                  R-squared       =     0.5366
                                                  Adj R-squared   =     0.5296
                                                  Within R-sq.    =     0.0019
Number of clusters (province_id) =        110     Root MSE        =     5.9436

                                         (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_neigh_treat_campaign |   .1314393   .0654738     2.01   0.047     .0016724    .2612061
                      _cons |   59.15748   .0841481   703.02   0.000      58.9907    59.32426
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est1 stored)

.         eststo: reghdfe referendum_no std_wn_neigh_treat_campaign `controls' if std_wn_treat_campaign==0, absorb(province_id)  clu
> ster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,186
Absorbing 1 HDFE group                            F(  10,    109) =     110.43
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6935
                                                  Adj R-squared   =     0.6883
                                                  Within R-sq.    =     0.3326
Number of clusters (province_id) =        110     Root MSE        =     4.7987

                                         (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_neigh_treat_campaign |   .0268164   .0406653     0.66   0.511     -.053781    .1074138
                   m5s_c_13 |   .2379327   .0472045     5.04   0.000     .1443749    .3314906
                    pd_c_13 |  -.5145737   .0315166   -16.33   0.000    -.5770385   -.4521089
                 turnout_13 |   .0099761   .0340678     0.29   0.770    -.0575451    .0774973
                     income |  -.0004594   .0001007    -4.56   0.000     -.000659   -.0002598
               unemployment |   .1773491   .0283577     6.25   0.000      .121145    .2335533
                 university |  -.2819836   .0593733    -4.75   0.000    -.3996596   -.1643076
                     no_edu |  -.1779025   .0220583    -8.07   0.000    -.2216212   -.1341837
                 foreigners |  -.0232989   .0348983    -0.67   0.506    -.0924662    .0458685
             pop_density_16 |   .0001896   .0001525     1.24   0.216    -.0001126    .0004918
                      _cons |   75.62316   2.119504    35.68   0.000     71.42237    79.82395
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est2 stored)

.         eststo: reghdfe referendum_no std_wn_neigh_treat_campaign, absorb(province_id) cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       3.93
Statistics robust to heteroskedasticity           Prob > F        =     0.0500
                                                  R-squared       =     0.5573
                                                  Adj R-squared   =     0.5511
                                                  Within R-sq.    =     0.0017
Number of clusters (province_id) =        110     Root MSE        =     5.8603

                                         (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_neigh_treat_campaign |   .1236429   .0623958     1.98   0.050    -.0000236    .2473094
                      _cons |   59.35013   .0863838   687.05   0.000     59.17892    59.52134
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est3 stored)

.         eststo: reghdfe referendum_no std_wn_neigh_treat_campaign `controls', absorb(province_id)  cluster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  10,    109) =     125.24
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7124
                                                  Adj R-squared   =     0.7080
                                                  Within R-sq.    =     0.3446
Number of clusters (province_id) =        110     Root MSE        =     4.6904

                                         (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_neigh_treat_campaign |    .015159   .0394817     0.38   0.702    -.0630924    .0934105
                   m5s_c_13 |   .2470569   .0512684     4.82   0.000     .1454446    .3486692
                    pd_c_13 |  -.5140582   .0334761   -15.36   0.000    -.5804067   -.4477096
                 turnout_13 |   .0012778   .0355825     0.04   0.971    -.0692455    .0718011
                     income |   -.000481   .0000942    -5.11   0.000    -.0006676   -.0002944
               unemployment |   .1785912   .0270343     6.61   0.000     .1250101    .2321724
                 university |  -.2464339   .0575785    -4.28   0.000    -.3605527   -.1323151
                     no_edu |  -.1836185   .0227072    -8.09   0.000    -.2286234   -.1386136
                 foreigners |  -.0217751   .0360424    -0.60   0.547      -.09321    .0496598
             pop_density_16 |   .0002489   .0001005     2.48   0.015     .0000497    .0004481
                      _cons |   76.38116    2.07032    36.89   0.000     72.27786    80.48447
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est4 stored)

.         eststo: reghdfe referendum_no std_wn_neigh_treat_campaign std_wn_treat_campaign, absorb(province_id) cluster(province_id)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   2,    109) =       4.10
Statistics robust to heteroskedasticity           Prob > F        =     0.0193
                                                  R-squared       =     0.5579
                                                  Adj R-squared   =     0.5517
                                                  Within R-sq.    =     0.0031
Number of clusters (province_id) =        110     Root MSE        =     5.8566

                                         (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_neigh_treat_campaign |   .1205892   .0616177     1.96   0.053    -.0015351    .2427136
      std_wn_treat_campaign |   .3371568   .1226697     2.75   0.007     .0940295    .5802842
                      _cons |    59.2945   .0971309   610.46   0.000     59.10199    59.48701
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est5 stored)

.         eststo: reghdfe referendum_no std_wn_neigh_treat_campaign std_wn_treat_campaign `controls', absorb(province_id)  cluster(p
> rovince_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  11,    109) =     114.96
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7127
                                                  Adj R-squared   =     0.7082
                                                  Within R-sq.    =     0.3451
Number of clusters (province_id) =        110     Root MSE        =     4.6890

                                         (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_neigh_treat_campaign |   .0160679   .0397852     0.40   0.687    -.0627851    .0949209
      std_wn_treat_campaign |   .2067176   .0767888     2.69   0.008     .0545247    .3589105
                   m5s_c_13 |   .2457353   .0514508     4.78   0.000     .1437616    .3477091
                    pd_c_13 |  -.5134436   .0334685   -15.34   0.000     -.579777   -.4471102
                 turnout_13 |   .0030754   .0357169     0.09   0.932    -.0677143     .073865
                     income |  -.0004796    .000094    -5.10   0.000    -.0006659   -.0002933
               unemployment |   .1775716    .027059     6.56   0.000     .1239415    .2312016
                 university |  -.2575636   .0575666    -4.47   0.000    -.3716588   -.1434684
                     no_edu |   -.182332   .0226256    -8.06   0.000    -.2271752   -.1374888
                 foreigners |  -.0235018   .0363533    -0.65   0.519    -.0955529    .0485493
             pop_density_16 |   .0002124   .0001013     2.10   0.038     .0000117    .0004131
                      _cons |    76.2737   2.060861    37.01   0.000     72.18914    80.35826
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est6 stored)

.         ***create a LaTeX Table:
.         estfe est*, labels(province_id "Province FE")

.         *
.         esttab est* using "$tables/taba8_adjacent_regional.tex", replace  ///
>         indicate( `r(indicate_fe)' "Controls=income", labels(\checkmark)) ///
>         se nobaselevels nostar label se(2) b(2) ///
>         drop(pd_c_13 turnout_13 unemployment university no_edu foreigners pop_density_16) ///
>         stats(N N_clust r2_a r2_a_within rmse, labels("Obs" "Provinces" "adj.R\$^2$" "adj.R\$^2$ (within)" "RMSE")) ///
>         note("\emph{Note:} Clustered standard errors by province in parentheses. Controls omitted from table: PD: \% votes 2013, \
> % turnout 2013, income per cap, \% unemployed, \% university degree, \% low education, \% foreigners, population density. Same var
> iables used for matching, history omitted from matching.") ///
>         substitute(_ _) 
(output written to /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/tables/taba8_adjacent_regional.tex)

.         
.         // adjacent municipalities (tab a9)
.         eststo clear 

.         eststo: reghdfe referendum_no std_wn_neigh_treat_campaign if std_wn_treat_campaign>0, noabsorb cluster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =        621
Absorbing 1 HDFE group                            F(   1,    102) =       2.80
Statistics robust to heteroskedasticity           Prob > F        =     0.0974
                                                  R-squared       =     0.0155
                                                  Adj R-squared   =     0.0139
                                                  Within R-sq.    =     0.0155
Number of clusters (province_id) =        103     Root MSE        =     9.2972

                                         (Std. err. adjusted for 103 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_neigh_treat_campaign |   .5552456   .3319139     1.67   0.097    -.1031041    1.213595
                      _cons |   60.41243   .9358863    64.55   0.000      58.5561    62.26875
---------------------------------------------------------------------------------------------
(est1 stored)

.         eststo: reghdfe referendum_no std_wn_neigh_treat_campaign `controls' if std_wn_treat_campaign>0, noabsorb cluster(province
> _id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =        618
Absorbing 1 HDFE group                            F(  10,    102) =     173.89
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8606
                                                  Adj R-squared   =     0.8583
                                                  Within R-sq.    =     0.8606
Number of clusters (province_id) =        103     Root MSE        =     3.5067

                                         (Std. err. adjusted for 103 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_neigh_treat_campaign |   .0197077   .0998712     0.20   0.844    -.1783864    .2178017
                   m5s_c_13 |    .239387   .0580206     4.13   0.000     .1243034    .3544707
                    pd_c_13 |  -.6289592   .0486191   -12.94   0.000    -.7253949   -.5325236
                 turnout_13 |  -.0308141    .055929    -0.55   0.583     -.141749    .0801209
                     income |  -.0008451   .0001697    -4.98   0.000    -.0011817   -.0005085
               unemployment |    .236142   .0575483     4.10   0.000     .1219951    .3502888
                 university |  -.2235941   .0781246    -2.86   0.005    -.3785538   -.0686344
                     no_edu |  -.4224776   .0646842    -6.53   0.000    -.5507784   -.2941768
                 foreigners |  -.2040512   .0593236    -3.44   0.001    -.3217194    -.086383
             pop_density_16 |  -.0000299   .0001129    -0.26   0.792    -.0002538     .000194
                      _cons |   94.15765   5.026971    18.73   0.000     84.18668    104.1286
---------------------------------------------------------------------------------------------
(est2 stored)

.         eststo: reghdfe referendum_no std_wn_neigh_treat_campaign if std_wn_treat_campaign>0, absorb(province_id) cluster(province
> _id) 
(dropped 17 singleton observations)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =        604
Absorbing 1 HDFE group                            F(   1,     85) =       0.03
Statistics robust to heteroskedasticity           Prob > F        =     0.8690
                                                  R-squared       =     0.8368
                                                  Adj R-squared   =     0.8097
                                                  Within R-sq.    =     0.0001
Number of clusters (province_id) =         86     Root MSE        =     4.0969

                                          (Std. err. adjusted for 86 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_neigh_treat_campaign |   .0249082   .1505983     0.17   0.869    -.2745216    .3243379
                      _cons |   61.80042   .3951493   156.40   0.000     61.01476    62.58608
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        86          86           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est3 stored)

.         eststo: reghdfe referendum_no std_wn_neigh_treat_campaign `controls' if std_wn_treat_campaign>0, absorb(province_id) clust
> er(province_id) 
(dropped 17 singleton observations)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =        601
Absorbing 1 HDFE group                            F(  10,     85) =     167.59
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9383
                                                  Adj R-squared   =     0.9267
                                                  Within R-sq.    =     0.6268
Number of clusters (province_id) =         86     Root MSE        =     2.5294

                                          (Std. err. adjusted for 86 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_neigh_treat_campaign |   .0053208   .0987992     0.05   0.957    -.1911184    .2017601
                   m5s_c_13 |    .195489   .0574756     3.40   0.001     .0812121    .3097659
                    pd_c_13 |  -.5066768   .0387908   -13.06   0.000    -.5838033   -.4295504
                 turnout_13 |  -.0422059   .0500613    -0.84   0.402    -.1417412    .0573293
                     income |  -.0006485   .0001809    -3.58   0.001    -.0010082   -.0002888
               unemployment |   .1385505   .0501513     2.76   0.007     .0388364    .2382647
                 university |  -.2891364   .0841003    -3.44   0.001    -.4563504   -.1219224
                     no_edu |  -.3227236   .0425387    -7.59   0.000    -.4073019   -.2381453
                 foreigners |  -.0353622   .0388107    -0.91   0.365    -.1125284    .0418039
             pop_density_16 |   .0001496   .0000823     1.82   0.073     -.000014    .0003131
                      _cons |   88.83945    4.61009    19.27   0.000     79.67336    98.00554
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |        86          86           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est4 stored)

.         eststo: reghdfe referendum_no std_wn_neigh_treat_campaign std_wn_treat_campaign if std_wn_treat_campaign>0, noabsorb clust
> er(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =        621
Absorbing 1 HDFE group                            F(   2,    102) =       5.29
Statistics robust to heteroskedasticity           Prob > F        =     0.0065
                                                  R-squared       =     0.0275
                                                  Adj R-squared   =     0.0244
                                                  Within R-sq.    =     0.0275
Number of clusters (province_id) =        103     Root MSE        =     9.2475

                                         (Std. err. adjusted for 103 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_neigh_treat_campaign |   .5126625   .3317626     1.55   0.125    -.1453871    1.170712
      std_wn_treat_campaign |   .9434345   .3340043     2.82   0.006     .2809385    1.605931
                      _cons |   58.36546   1.344203    43.42   0.000     55.69924    61.03167
---------------------------------------------------------------------------------------------
(est5 stored)

.         eststo: reghdfe referendum_no std_wn_neigh_treat_campaign std_wn_treat_campaign `controls' if std_wn_treat_campaign>0, noa
> bsorb cluster(province_id) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =        618
Absorbing 1 HDFE group                            F(  11,    102) =     158.36
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8613
                                                  Adj R-squared   =     0.8588
                                                  Within R-sq.    =     0.8613
Number of clusters (province_id) =        103     Root MSE        =     3.5002

                                         (Std. err. adjusted for 103 clusters in province_id)
---------------------------------------------------------------------------------------------
                            |               Robust
              referendum_no | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
std_wn_neigh_treat_campaign |   .0078682   .0963927     0.08   0.935    -.1833262    .1990627
      std_wn_treat_campaign |    .235558   .1701285     1.38   0.169     -.101891    .5730071
                   m5s_c_13 |   .2392261   .0577542     4.14   0.000     .1246709    .3537812
                    pd_c_13 |  -.6261562   .0490233   -12.77   0.000    -.7233936   -.5289188
                 turnout_13 |  -.0283832    .054974    -0.52   0.607    -.1374239    .0806575
                     income |  -.0008397   .0001658    -5.06   0.000    -.0011685   -.0005108
               unemployment |    .239456    .058052     4.12   0.000     .1243101    .3546019
                 university |  -.2245703   .0773284    -2.90   0.005    -.3779508   -.0711898
                     no_edu |  -.4168591   .0655791    -6.36   0.000    -.5469351   -.2867832
                 foreigners |  -.2039103   .0587682    -3.47   0.001    -.3204768   -.0873438
             pop_density_16 |  -8.77e-06   .0001087    -0.08   0.936    -.0002244    .0002068
                      _cons |   93.13584   5.194431    17.93   0.000     82.83272     103.439
---------------------------------------------------------------------------------------------
(est6 stored)

.         *eststo: reghdfe referendum_no std_wn_neigh_treat_campaign std_wn_treat_campaign m5s_c_13 pd_c_13 turnout income unemploym
> ent university no_edu foreigners pop_density_16 if std_wn_treat_campaign>0, absorb(province_id) cluster(province_id) 
.         ***create a LaTeX Table:
.         estfe est*, labels(province_id "Province FE")

.         *
.         esttab est* using "$tables/taba9_ONLYadjacent_regional.tex", replace  ///
>         indicate( `r(indicate_fe)' "Controls=income", labels(\checkmark)) ///
>         se nobaselevels nostar label se(2) b(2) ///
>         noconstant nogaps ///
>         drop(pd_c_13 turnout_13 unemployment university no_edu foreigners pop_density_16) ///
>         stats(N N_clust r2_a r2_a_within rmse, labels("Obs" "Provinces" "adj.R\$^2$" "adj.R\$^2$ (within)" "RMSE") fmt(%9.0f %9.0f
>  %9.2f %9.2f %9.2f)) ///
>         note("\emph{Note:} Clustered standard errors by province in parentheses. Controls omitted from table: PD: \% votes 2013, \
> % turnout 2013, income per cap, \% unemployed, \% university degree, \% low education, \% foreigners, population density. Same var
> iables used for matching, history omitted from matching.") ///
>         substitute(_ _) 
(output written to /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/tables/taba9_ONLYadjacent_regional.tex)

.         
. 
.         // effect of M5S on other referendum outcomes, Yes + Turnout (fig a10)
.         cls

.         eststo clear

.         foreach var of varlist referendum_yes turnout {
  2.                 eststo: reghdfe `var' std_wn_treat_campaign, noabsorb cluster(province_id)
  3.                 eststo: reghdfe `var' std_wn_treat_campaign, absorb(province_id) cluster(province_id)
  4.                 eststo: reghdfe `var' std_wn_treat_campaign `controls', absorb(province_id)  cluster(province_id) 
  5.                 ebalance m5s_ref_ever `controls'
  6.                 eststo: reghdfe `var' std_wn_treat_campaign [aweight=_webal], absorb(province_id) cluster(province_id)
  7.         }
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       6.42
Statistics robust to heteroskedasticity           Prob > F        =     0.0127
                                                  R-squared       =     0.0062
                                                  Adj R-squared   =     0.0061
                                                  Within R-sq.    =     0.0062
Number of clusters (province_id) =        110     Root MSE        =     8.6567

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
       referendum_yes | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.9990272   .3942926    -2.53   0.013    -1.780502   -.2175522
                _cons |   39.62872   .6563295    60.38   0.000      38.3279    40.92954
---------------------------------------------------------------------------------------
(est1 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       5.09
Statistics robust to heteroskedasticity           Prob > F        =     0.0261
                                                  R-squared       =     0.5579
                                                  Adj R-squared   =     0.5517
                                                  Within R-sq.    =     0.0009
Number of clusters (province_id) =        110     Root MSE        =     5.8138

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
       referendum_yes | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.2765848   .1226278    -2.26   0.026    -.5196291   -.0335405
                _cons |   39.50046   .0217707  1814.39   0.000     39.45731    39.54361
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est2 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  10,    109) =     121.66
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7110
                                                  Adj R-squared   =     0.7066
                                                  Within R-sq.    =     0.3391
Number of clusters (province_id) =        110     Root MSE        =     4.6673

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
       referendum_yes | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.1883427   .0762823    -2.47   0.015    -.3395317   -.0371537
             m5s_c_13 |  -.2355751   .0513718    -4.59   0.000    -.3373923   -.1337579
              pd_c_13 |   .5081676   .0330684    15.37   0.000     .4426272    .5737081
           turnout_13 |   -.005796   .0356645    -0.16   0.871    -.0764819    .0648898
               income |   .0004845   .0000933     5.19   0.000     .0002996    .0006693
         unemployment |  -.1759672   .0265513    -6.63   0.000    -.2285911   -.1233434
           university |   .2713005   .0575094     4.72   0.000     .1573187    .3852823
               no_edu |   .1680199   .0222225     7.56   0.000     .1239757    .2120641
           foreigners |   .0249563   .0360477     0.69   0.490     -.046489    .0964016
       pop_density_16 |  -.0001799   .0001019    -1.76   0.080     -.000382    .0000221
                _cons |   23.07576   2.092539    11.03   0.000     18.92842     27.2231
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est3 stored)


Data Setup
Treatment variable:   m5s_ref_ever
Covariate adjustment: m5s_c_13 pd_c_13 turnout_13 income unemployment university no_edu foreigners pop_density_16 

Optimizing...
Iteration 1: Max Difference = 53677.9914
Iteration 2: Max Difference = 19745.0605
Iteration 3: Max Difference = 7261.83395
Iteration 4: Max Difference = 2669.51473
Iteration 5: Max Difference = 980.103505
Iteration 6: Max Difference = 358.627005
Iteration 7: Max Difference = 130.059951
Iteration 8: Max Difference = 46.130041
Iteration 9: Max Difference = 15.5962515
Iteration 10: Max Difference = 4.93874248
Iteration 11: Max Difference = 1.5460966
Iteration 12: Max Difference = .35475118
Iteration 13: Max Difference = .02493076
Iteration 14: Max Difference = .000123282
maximum difference smaller than the tolerance level; convergence achieved


Treated units: 619     total of weights: 619
Control units: 7189    total of weights: 619


Before: without weighting

             |              Treat              |             Control             
             |      mean   variance   skewness |      mean   variance   skewness 
-------------+---------------------------------+---------------------------------
    m5s_c_13 |     20.75      21.51      .2074 |      18.3      35.11     .03357 
     pd_c_13 |      19.5       53.4      1.046 |      18.6       42.1       .702 
  turnout_13 |     74.54      49.11     -.7995 |     74.68      61.76      -.954 
      income |     11955   1.20e+07      .2146 |     11995    9083129     .04957 
unemployment |     13.22      45.64       .736 |     10.07       38.7      1.257 
  university |     9.366      12.36      1.069 |     6.903      5.614      1.146 
      no_edu |     28.56      30.83      .7078 |     33.66      57.14      1.063 
  foreigners |     7.465      21.47      .5777 |     6.556      19.47      1.011 
pop_densi~16 |     891.1    1834514      3.897 |     259.1     282806      7.436 


After:  _webal as the weighting variable

             |              Treat              |             Control             
             |      mean   variance   skewness |      mean   variance   skewness 
-------------+---------------------------------+---------------------------------
    m5s_c_13 |     20.75      21.51      .2074 |     20.75      30.74      .2474 
     pd_c_13 |      19.5       53.4      1.046 |      19.5      38.15      .8164 
  turnout_13 |     74.54      49.11     -.7995 |     74.54      56.69     -.9325 
      income |     11955   1.20e+07      .2146 |     11955   1.50e+07      1.027 
unemployment |     13.22      45.64       .736 |     13.22      58.19      .8788 
  university |     9.366      12.36      1.069 |     9.366       15.6      1.594 
      no_edu |     28.56      30.83      .7078 |     28.56      33.84      .5679 
  foreigners |     7.465      21.47      .5777 |     7.465      29.87      1.226 
pop_densi~16 |     891.1    1834514      3.897 |     891.1    3468613      3.859 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(   1,    109) =       3.69
Statistics robust to heteroskedasticity           Prob > F        =     0.0574
                                                  R-squared       =     0.7267
                                                  Adj R-squared   =     0.7228
                                                  Within R-sq.    =     0.0020
Number of clusters (province_id) =        110     Root MSE        =     4.6742

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
       referendum_yes | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.1664436   .0866612    -1.92   0.057    -.3382034    .0053161
                _cons |   37.72914   .0990138   381.05   0.000      37.5329    37.92538
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est4 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       3.62
Statistics robust to heteroskedasticity           Prob > F        =     0.0599
                                                  R-squared       =     0.0020
                                                  Adj R-squared   =     0.0019
                                                  Within R-sq.    =     0.0020
Number of clusters (province_id) =        110     Root MSE        =     8.6572

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
              turnout | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.5686806   .2990615    -1.90   0.060    -1.161411    .0240496
                _cons |   68.57393     .83346    82.28   0.000     66.92204    70.22582
---------------------------------------------------------------------------------------
(est5 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,994
Absorbing 1 HDFE group                            F(   1,    109) =       4.59
Statistics robust to heteroskedasticity           Prob > F        =     0.0345
                                                  R-squared       =     0.7190
                                                  Adj R-squared   =     0.7151
                                                  Within R-sq.    =     0.0010
Number of clusters (province_id) =        110     Root MSE        =     4.6251

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
              turnout | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |   .2314012   .1080514     2.14   0.034     .0172468    .4455555
                _cons |   68.43189   .0191829  3567.34   0.000     68.39387    68.46991
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est6 stored)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(  10,    109) =     196.79
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8751
                                                  Adj R-squared   =     0.8731
                                                  Within R-sq.    =     0.5401
Number of clusters (province_id) =        110     Root MSE        =     3.0902

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
              turnout | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.1708161   .0581578    -2.94   0.004     -.286083   -.0555492
             m5s_c_13 |   .1093809   .0260287     4.20   0.000     .0577928    .1609689
              pd_c_13 |   .0587999   .0147281     3.99   0.000     .0296094    .0879905
           turnout_13 |   .5322744   .0209852    25.36   0.000     .4906824    .5738664
               income |   .0001801   .0000481     3.74   0.000     .0000848    .0002754
         unemployment |  -.0327232   .0196578    -1.66   0.099    -.0716843     .006238
           university |   .0993588   .0352563     2.82   0.006      .029482    .1692357
               no_edu |  -.0558045   .0130692    -4.27   0.000    -.0817073   -.0299017
           foreigners |  -.0530694    .016909    -3.14   0.002    -.0865825   -.0195563
       pop_density_16 |  -.0001096   .0000824    -1.33   0.186     -.000273    .0000538
                _cons |   25.28253   1.901154    13.30   0.000     21.51451    29.05056
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est7 stored)


Data Setup
Treatment variable:   m5s_ref_ever
Covariate adjustment: m5s_c_13 pd_c_13 turnout_13 income unemployment university no_edu foreigners pop_density_16 

Optimizing...
Iteration 1: Max Difference = 53677.9914
Iteration 2: Max Difference = 19745.0605
Iteration 3: Max Difference = 7261.83395
Iteration 4: Max Difference = 2669.51473
Iteration 5: Max Difference = 980.103505
Iteration 6: Max Difference = 358.627005
Iteration 7: Max Difference = 130.059951
Iteration 8: Max Difference = 46.130041
Iteration 9: Max Difference = 15.5962515
Iteration 10: Max Difference = 4.93874248
Iteration 11: Max Difference = 1.5460966
Iteration 12: Max Difference = .35475118
Iteration 13: Max Difference = .02493076
Iteration 14: Max Difference = .000123282
maximum difference smaller than the tolerance level; convergence achieved


Treated units: 619     total of weights: 619
Control units: 7189    total of weights: 619


Before: without weighting

             |              Treat              |             Control             
             |      mean   variance   skewness |      mean   variance   skewness 
-------------+---------------------------------+---------------------------------
    m5s_c_13 |     20.75      21.51      .2074 |      18.3      35.11     .03357 
     pd_c_13 |      19.5       53.4      1.046 |      18.6       42.1       .702 
  turnout_13 |     74.54      49.11     -.7995 |     74.68      61.76      -.954 
      income |     11955   1.20e+07      .2146 |     11995    9083129     .04957 
unemployment |     13.22      45.64       .736 |     10.07       38.7      1.257 
  university |     9.366      12.36      1.069 |     6.903      5.614      1.146 
      no_edu |     28.56      30.83      .7078 |     33.66      57.14      1.063 
  foreigners |     7.465      21.47      .5777 |     6.556      19.47      1.011 
pop_densi~16 |     891.1    1834514      3.897 |     259.1     282806      7.436 


After:  _webal as the weighting variable

             |              Treat              |             Control             
             |      mean   variance   skewness |      mean   variance   skewness 
-------------+---------------------------------+---------------------------------
    m5s_c_13 |     20.75      21.51      .2074 |     20.75      30.74      .2474 
     pd_c_13 |      19.5       53.4      1.046 |      19.5      38.15      .8164 
  turnout_13 |     74.54      49.11     -.7995 |     74.54      56.69     -.9325 
      income |     11955   1.20e+07      .2146 |     11955   1.50e+07      1.027 
unemployment |     13.22      45.64       .736 |     13.22      58.19      .8788 
  university |     9.366      12.36      1.069 |     9.366       15.6      1.594 
      no_edu |     28.56      30.83      .7078 |     28.56      33.84      .5679 
  foreigners |     7.465      21.47      .5777 |     7.465      29.87      1.226 
pop_densi~16 |     891.1    1834514      3.897 |     891.1    3468613      3.859 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      7,804
Absorbing 1 HDFE group                            F(   1,    109) =       5.86
Statistics robust to heteroskedasticity           Prob > F        =     0.0171
                                                  R-squared       =     0.7766
                                                  Adj R-squared   =     0.7734
                                                  Within R-sq.    =     0.0077
Number of clusters (province_id) =        110     Root MSE        =     3.9475

                                   (Std. err. adjusted for 110 clusters in province_id)
---------------------------------------------------------------------------------------
                      |               Robust
              turnout | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
std_wn_treat_campaign |  -.2788801   .1151958    -2.42   0.017    -.5071944   -.0505658
                _cons |   67.88259   .1316156   515.76   0.000     67.62173    68.14345
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 province_id |       110         110           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est8 stored)

. 
.         *
.         coefplot ///
>         est1 est2 est3 est4, legend(off) bylabel("{bf:Referendum: 'Yes'}")  ///
>         || ///
>         est5 est6 est7 est8,    /// 
>         drop(_cons) ///
>         ciopts(lwidth(0.4 ..)) mlwidth(medthick) msize(medsmall) mfcolor(white) ///
>         byopts(legend(off)) ///
>         bylabel("{bf:Referendum: turnout}") ///
>         xline(0)  ///
>         grid(none) ///
>         ylabel( ///
>         1 "{bf:M5S: referendum}" ///
>         2 "M5S: % votes 2013" ///
>         3 "PD: % votes 2013" ///
>         4 "% turnout 2013" ///
>         5 "income per cap" ///
>         6 "% unemployed"  ///
>         7 "% university" ///
>         8  "% low education" ///
>         9 "% foreigners" /// 
>         10 "population density" /// 
>         )

.         * save as pdf: 
.         graph export "$figures/figa10_ty_regional.pdf", replace
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/figa10_ty_regional.pdf saved as PDF format

. 
.         // Indoor vs. Outdoor (Fig a12)
.         summarize wn_treat_loc_indoor if wn_treat_loc_indoor>0

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
wn_tre~ndoor |        321    71.19626    150.9314          1       1774

.         local m_in=r(mean)

.         local m_in=round(`m_in', 0.01)

.         summarize wn_treat_loc_outdoor if wn_treat_loc_outdoor>0

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
wn_tre~tdoor |        285    46.41404    98.23296          1       1059

.         local m_out=r(mean)

.         local m_out=round(`m_out', 0.01)

.         * histogram:
.         histogram wn_treat_loc_indoor if wn_treat_loc_indoor>0, ///
>         col(uzhblue%50) xtitle("RSVPs for ...") legend(order(1 "indoor" 2 "outdoor")) ///
>         addplot(histogram wn_treat_loc_outdoor if wn_treat_loc_outdoor>0, col(uzhred2%50)) ///
>         xline(`m_in', lcol(uzhblue)) xline( `m_out', lcol(uzhred2)) ///
>         text(0 `m_in' " `m_in' ", place(e) col(uzhblue) size(small)) text(0  `m_out' " `m_out' ", place(w) col(uzhred2) size(small
> ))
(bin=17, start=1, width=104.29412)

.         * save as pdf: 
.         graph export "$figures/figa12_inout.pdf", replace
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/figa12_inout.pdf saved as PDF format

. 
. 
.         // Indoor vs. Outdoor (Fig a13)
.         summarize n_treat_loc_indoor if n_treat_loc_indoor>0

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
n_trea~ndoor |        321    12.29283    25.10083          1        363

.         local m_in=r(mean)

.         local m_in=round(`m_in', 0.01)

.         summarize n_treat_loc_outdoor if n_treat_loc_outdoor>0

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
n_trea~tdoor |        287    8.473868    12.98756          1        104

.         local m_out=r(mean)

.         local m_out=round(`m_out', 0.01)

.         * histogram: 
.         histogram n_treat_loc_indoor if n_treat_loc_indoor>0, ///
>         col(uzhblue%50) xtitle("Events ...") legend(order(1 "indoor" 2 "outdoor")) ///
>         addplot(histogram n_treat_loc_outdoor if n_treat_loc_outdoor>0, col(uzhred2%50)) ///
>         xline(`m_in', lcol(uzhblue)) xline( `m_out', lcol(uzhred2)) ///
>         text(0 `m_in' " `m_in' ", place(e) col(uzhblue) size(small)) text(0  `m_out' " `m_out' ", place(w) col(uzhred2) size(small
> ))
(bin=17, start=1, width=21.294118)

.         * save as pdf: 
.         graph export "$figures/figa13_inout.pdf", replace
file /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/figures/figa13_inout.pdf saved as PDF format

.         ** create a LaTeX Table:
.         estfe est*, labels(post "Wave FE" comune_id "Municipality FE" province_id "Province FE")

. 
.         // summary statistics (tab a12) 
.         est clear  

.         
.         estpost tabstat referendum_no m5s_ref_ever std_wn_treat_campaign ///
>         `controls' ///
>         std_wn_treat_campaign_short std_wn_neigh_treat_campaign  km_to_ugs hist_days std_wn_posttreat std_wn_treat_loc_indoor std_
> wn_treat_loc_outdoor ///
>         , ///
>         c(stat) stat(mean sd min max n)

Summary statistics: mean sd min max count
     for variables: referendum_no m5s_ref_ever std_wn_treat_campaign m5s_c_13 pd_c_13 turnout_13 income unemployment university no_e
> du foreigners pop_density_16 std_wn_treat_campaign_short std_wn_neigh_treat_campaign km_to_ugs hist_days std_wn_posttreat std_wn_t
> reat_loc_indoor std_wn_treat_loc_outdoor

             |   e(mean)      e(sd)     e(min)     e(max)   e(count) 
-------------+-------------------------------------------------------
referendum~o |   59.5213   8.747091   14.83771   88.23529       7994 
m5s_ref_ever |  .0777694   .2678252          0          1       7998 
std_wn_tre~n |  .1775348   .6835371          0   6.513209       7994 
    m5s_c_13 |  18.41984   5.905199   .1269035   49.86737       7939 
     pd_c_13 |  18.58854    6.59277    .877193   53.48315       7939 
  turnout_13 |  74.60424     7.8513   20.34162        100       7939 
      income |  12024.69   3049.701   3111.275   29210.04       7998 
unemployment |   10.2589   6.315525        .64      42.18       7913 
  university |    7.0838   2.575059   .5714286   27.01579       7939 
      no_edu |  33.27854   7.604208   9.013685   85.83639       7832 
  foreigners |  6.602878    4.45668          0      33.75       7965 
pop_densi~16 |  303.3014   652.7831     .75243   12972.39       7998 
std_wn_tre~t |  .1066934   .4520167          0   4.958238       7994 
std_wn_nei~n |  1.384449   2.161674          0   9.974855       7994 
   km_to_ugs |  14.09584    8.93809          0   212.0234       7938 
   hist_days |  132.8756   522.9766          0       4148       7998 
std_wn_pos~t |  .1928973   .7299391          0    5.75632       7994 
std_wn_tre.. |  .0513615   .3056345          0   4.457923       7994 
std_wn_tre.. |  .0357697   .2270157          0   3.770525       7994 

.         
.         esttab using "$tables/taba12_summary_regional.tex", replace ///
>         cells("mean(fmt(%13.2fc)) sd(fmt(%13.2fc)) min max count") nonumber ///
>         nomtitle nonote noobs label collabels("Mean" "SD" "Min" "Max" "N")
(output written to /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/results/tables/taba12_summary_regional.tex)

. 
. 
end of do-file
      name:  plog_30
       log:  /Users/au660280/Dropbox/m5S/JoP_PlaceBasedCampaigning_replication/code/do/09_analysis_regional.log
  log type:  text
 closed on:  19 Sep 2022, 11:40:25
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